UWB Radar System for Breath Activity Monitoring

SAPIENZA University of Rome

Dottorato di Ricerca in Ingegneria Elettronica

XXIII Ciclo

UWB Radar Systemfor Breath Activity Monitoring

Erika Pittella

Department of Information Engineering,

Electronics and Telecommunications


December 2010


Dottorato di Ricerca in Ingegneria Elettronica

XXIII Ciclo

UWB Radar Systemfor Breath Activity Monitoring

Erika Pittella

Advisor Co-Advisor

Prof. Stefano Pisa Prof. Marco Balsi

AUTHOR’S ADDRESS:

Erika Pittella

Department of Information Engineering,

Electronics and Telecommunications

Via Eudossiana 18, 00184 Rome

e-mail: [email protected]

Contents

Introduction 1

Motivation 4

Outline 5

Contributions 6

Publications 6

Collaborations 8

I Ultra Wideband Radar Systems 9

1 Introduction to UWB

Radio and Radar Systems 11

1.1 Historical Background . . . . . . . . . . . . . . . . . . . . . . 13

1.2 Regulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1.2.1 United States Regulations . . . . . . . . . . . . . . . . 17

1.2.2 European Regulations . . . . . . . . . . . . . . . . . . 23

1.2.3 Japanese Regulations . . . . . . . . . . . . . . . . . . . 25

2 UWB Radars 27

2.1 UWB Radar Scheme . . . . . . . . . . . . . . . . . . . . . . . 28

2.2 UWB Radar Features . . . . . . . . . . . . . . . . . . . . . . . 29

2.2.1 Repetition Rate . . . . . . . . . . . . . . . . . . . . . . 29

i

2.2.2 Range . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.2.3 Resolution . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.2.4 Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . 34

3 Breath Activity Monitoring Systems 37

3.1 Medical Applications of UWB Radars . . . . . . . . . . . . . . 37

3.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

II Circuit Model for the Design of a UWB RadarSystem 51

4 UWB Radar Model 53

4.1 Circuit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.2 Numerical Validation . . . . . . . . . . . . . . . . . . . . . . . 58

4.2.1 Model Parameter Extraction . . . . . . . . . . . . . . . 59

4.2.2 Validation Results . . . . . . . . . . . . . . . . . . . . 61

4.3 Experimental Validation . . . . . . . . . . . . . . . . . . . . . 65

4.3.1 Experimental Set-Up . . . . . . . . . . . . . . . . . . . 66

4.3.2 Model Parameter Extraction . . . . . . . . . . . . . . . 68

4.3.3 Experimental Results . . . . . . . . . . . . . . . . . . . 70

5 Feasibility Study 73

5.1 Meeting the FCC mask . . . . . . . . . . . . . . . . . . . . . . 73

5.1.1 Antenna Parameter Extraction . . . . . . . . . . . . . 74

5.1.2 Source Parameter Extraction . . . . . . . . . . . . . . 74

5.2 Human Body Radar Cross Section . . . . . . . . . . . . . . . . 76

5.3 Breath Activity Responses . . . . . . . . . . . . . . . . . . . . 82

5.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

III Subsystem Design 85

Description of the UWB Radar Scheme 87

ii

6 UWB Sources 89

6.1 Impulse Generation . . . . . . . . . . . . . . . . . . . . . . . . 89

6.1.1 Semiconductor Impulse Generator . . . . . . . . . . . . 90

6.1.2 Non Linear Transmission Lines . . . . . . . . . . . . . 91

6.2 Step Recovery Diodes . . . . . . . . . . . . . . . . . . . . . . . 92

6.2.1 Qualitative Analysis . . . . . . . . . . . . . . . . . . . 92

6.2.2 Quantitative Analysis . . . . . . . . . . . . . . . . . . . 95

6.2.3 Microwave Office Model . . . . . . . . . . . . . . . . . 97

6.3 UWB Source Design . . . . . . . . . . . . . . . . . . . . . . . 97

6.3.1 Gaussian Pulse Source . . . . . . . . . . . . . . . . . . 98

6.3.2 Monocycle Pulse Source . . . . . . . . . . . . . . . . . 103

6.3.3 Higher Order Derivatives Source . . . . . . . . . . . . . 108

6.4 Realization and Measurement Results . . . . . . . . . . . . . . 110

6.4.1 Gaussian Pulse Source . . . . . . . . . . . . . . . . . . 111

6.4.2 Monocycle Pulse Source . . . . . . . . . . . . . . . . . 111

7 UWB Antennas 115

7.1 Antenna Design . . . . . . . . . . . . . . . . . . . . . . . . . . 115

7.2 Antenna for Fixed UWB Systems . . . . . . . . . . . . . . . . 116

7.2.1 Antenna Performances in Free Space . . . . . . . . . . 117

7.3 Antenna for Wearable UWB Systems . . . . . . . . . . . . . . 121

7.3.1 Wearable Antenna Performances in the Presence of a

Box Model of the Thorax . . . . . . . . . . . . . . . . 121

7.4 Measurement Results . . . . . . . . . . . . . . . . . . . . . . . 123

7.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

8 UWB Receivers 127

8.1 UWB Receiver Schemes . . . . . . . . . . . . . . . . . . . . . 128

8.2 Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130

8.3 Complete Model Simulations . . . . . . . . . . . . . . . . . . . 133

8.4 Receiver Layout . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Conclusions and Future Directions 139

iii

List of Figures

1 Cardio-respiratory monitoring conventional techniques: spirom-

etry (a), ECG (b). . . . . . . . . . . . . . . . . . . . . . . . . 2

2 Remote sensing of human vital signs. . . . . . . . . . . . . . . 3

1.1 (a) Scheme of Hertz experimental set-up ; (b) Nikola Tesla’s

spark-gap transmitter. . . . . . . . . . . . . . . . . . . . . . . 14

1.2 FCC first guidelines on UWB technology. . . . . . . . . . . . . 18

1.3 FCC indoor (a) and outdoor (b) emission mask. . . . . . . . . 21

1.4 Emission limits issued by EC in 2009. . . . . . . . . . . . . . . 25

1.5 Proposed UWB japanese mask. . . . . . . . . . . . . . . . . . 26

2.1 Basic scheme of an impulse radar. . . . . . . . . . . . . . . . . 29

2.2 Radar slant range and ground range. . . . . . . . . . . . . . . 31

3.1 Block diagram of the UWB radar motion sensor. . . . . . . . . 38

3.2 MIR radar block scheme. . . . . . . . . . . . . . . . . . . . . . 39

3.3 MIR received signal and conventional electrocardiogram trace. 40

3.4 Staderini human tissues model. . . . . . . . . . . . . . . . . . 41

3.5 Simplified block scheme of Immoreev UWB radar. . . . . . . . 42

3.6 Pourvoyeur UWB radar test set up. . . . . . . . . . . . . . . . 43

3.7 Breath activity monitoring measurement set up. . . . . . . . . 44

3.8 Yeap test set up. . . . . . . . . . . . . . . . . . . . . . . . . . 44

3.9 Block diagram of the transceiver. . . . . . . . . . . . . . . . . 45

3.10 Block diagram of the fully integrated UWB radar for the de-

tection of heart and breath rates proposed by Zito et al. . . . 46

3.11 Dederer et al. block diagram system. . . . . . . . . . . . . . . 47

iv

3.12 Block diagram of Leib et al. UWB radar system. . . . . . . . 47

4.1 Scheme of the UWB radar system model. . . . . . . . . . . . . 54

4.2 Circuit model of the UWB radar system as implemented within

MWO. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

4.3 Scheme of the considered simplified scenario. . . . . . . . . . . 59

4.4 Radiation impedance (a) and effective length (b) of the dipole

obtained by means of numerical simulations with MWS as a

function of the frequency. . . . . . . . . . . . . . . . . . . . . . 60

4.5 Comparison between the MWS simulated and the analytical

Eq. 4.9 absolute values of SRRCS of the considered PEC panel

(a); simulated phase of the panel SRRCS as a function of the

frequency (b). . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

4.6 Comparison between the electric field 80 cm away from the

dipole achieved with the model and by means of simulations

with an exciting Gaussian pulse (a) σ = 250 ps, (b) σ =

125 ps, and (c) IGS with σ = 300 ps. . . . . . . . . . . . . . . 62

4.7 Time (a) and frequency (b) behaviors of the received voltage

at the dipole feed, achieved with the model and by means of

electromagnetic simulations, after the reflection from the PEC

panel 1 m away from the antenna. Exciting Gaussian pulse

with σ = 250 ps. . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.8 Comparison between the received signal at the dipole feed,

achieved with the model and by means of simulations, after

the reflection from the PEC panel 1 m away from the antenna.

Exciting Gaussian pulse with σ = 125 ps (a); IGS with σ =

300 ps (b). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64


at the dipole feed, achieved with the model and by means

of simulations, when a transversally indefinite wall is present

between the antenna and the target. Exciting Gaussian pulse

with σ = 250 ps. . . . . . . . . . . . . . . . . . . . . . . . . . 65

4.10 Scheme of an indirect UWB system. . . . . . . . . . . . . . . . 66

v

4.11 Flow chart of the operation performed by the indirect TDR

system operating as UWB radar. . . . . . . . . . . . . . . . . 67

4.12 Conical dipole radiation impedance (a) and effective length (b). 69


at the conical dipole feed, achieved with the model and by

measurements, after the reflection from the PEC panel 50 cm

away from the antenna. Exciting Gaussian pulse with σ = 250

ps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

4.14 Received signal from the copper panel 50 cm far away from

the antenna, using as excitation signal a monocycle pulse. . . . 71

5.1 Computed EIRP in function of the various input signals. . . . 75

5.2 Computed EIRP in function of V0 and RR. . . . . . . . . . . . 76

5.3 Scaled visible human (VH) model. . . . . . . . . . . . . . . . . 77

5.4 Visible human lungs geometry. . . . . . . . . . . . . . . . . . . 78

5.5 Exhalation (a) and inhalation phases (b). . . . . . . . . . . . . 79

5.6 Anatomic axial image (a); VH numerical dataset (b); VH sec-

tion 144 depicted by Matlab (c). . . . . . . . . . . . . . . . . . 79

5.7 Lung cells in function of the sections. . . . . . . . . . . . . . . 80

5.8 Frequency behavior of SRRCS absolute value in the RS respi-

ratory phase. . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

5.9 Comparison of the received signals during the RS phase by

using the smooth and the exponential approximation of the

SRRCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

5.10 Received signals by considering the three human models cor-

responding to RS, TB, and DB respiration phases . . . . . . . 83

5.11 Block scheme of the UWB radar system for breath activity

monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

6.1 Block scheme for the realization of UWB pulses. . . . . . . . . 89

6.2 Block scheme for the realization of UWB pulses. . . . . . . . . 90

6.3 NLTL effect on the wave front. . . . . . . . . . . . . . . . . . 91

6.4 Forward biased SRD. . . . . . . . . . . . . . . . . . . . . . . . 93

6.5 SRD discharge. . . . . . . . . . . . . . . . . . . . . . . . . . . 93

vi

6.6 Inverse biased SRD. . . . . . . . . . . . . . . . . . . . . . . . . 94

6.7 SRD element options. . . . . . . . . . . . . . . . . . . . . . . . 98

6.8 Realistic model of the SRD considering the package capaci-

tance and inductance. . . . . . . . . . . . . . . . . . . . . . . 98

6.9 UWB Gaussian pulse generation circuit. . . . . . . . . . . . . 99

6.10 UWB Gaussian pulse MWO circuit. . . . . . . . . . . . . . . . 100

6.11 Output voltage of the circuit schematic in Fig. 6.10 . . . . . . 100

6.12 Layout schematic of the MWO implementation of the Gaus-

sian pulse. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

6.13 Input and output voltage of the circuit schematic in Fig. 6.12. 102

6.14 Output voltage zoom of the layout schematic in Fig. 6.12. . . 103

6.15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

6.16 MWO circuit for the generation of a monocycle pulse. . . . . . 105

6.17 Behavior of the output monocycle voltage. . . . . . . . . . . . 105

6.18 Layout schematic of the MWO implementation of the mono-

cycle pulse. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

6.19 Comparison between the output voltage obtained with the cir-

cuit schematic and with the layout schematic. . . . . . . . . . 106

6.20 Circuit for the generation of the monocycle with the short

circuited stub. . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

6.21 Time behavior of the generated monocycle pulse. . . . . . . . 108

6.22 Layout schematic of the MWO implementation of the mono-

cycle pulse with two short circuited transmission lines. . . . . 109

6.23 Time behavior of the generated monocycle pulse. . . . . . . . 109

6.24 Time behaviors of the signal obtained with the designed UWB

source and with the analytical expression. . . . . . . . . . . . 110

6.25 Measurements experimental set-up. . . . . . . . . . . . . . . . 111

6.26 Realized device for the generation of the UWB Gaussian pulse

(a); measurement results (b). . . . . . . . . . . . . . . . . . . 112

6.27 Realized device for the generation of the UWB monocycle im-

pulse (a); measurement results (b). . . . . . . . . . . . . . . . 112

6.28 Realized device for the generation of the UWB monocycle im-

pulse (a); measurement results (b). . . . . . . . . . . . . . . . 113

vii

7.1 Geometry of the proposed antenna. . . . . . . . . . . . . . . . 117

7.2 Return loss of the proposed antenna. . . . . . . . . . . . . . . 117

7.3 Polar plot of the gain at 8 GHz for the fixed antenna. . . . . . 118

7.4 Polar plot of the gain at 4, 6 , 8, 10 GHz for the fixed antenna. 118

7.5 Peak gain behavior of the fixed system antenna and direction

of maximum gain as a function of the frequency. . . . . . . . . 119

7.6 Group delay of the proposed fixed system antenna. . . . . . . 121

7.7 Antenna in presence of biological tissues. . . . . . . . . . . . . 122

7.8 Received signals for two cardiac phases. . . . . . . . . . . . . . 123

7.9 Realized UWB antennas . . . . . . . . . . . . . . . . . . . . . 124

7.10 Measured and simulated return loss of the proposed antenna. . 124

7.11 Measured and simulated return loss of the proposed antenna. . 125

8.1 Receiver scheme by McEwan implemented in MWO. . . . . . . 129

8.2 Receiver scheme by Lee implemented in MWO. . . . . . . . . 129

8.3 Optimized receiver scheme implemented in MWO. . . . . . . . 132

8.4 Integrated signal behavior for different values of the capacitor. 132

8.5 Integrated signal behavior with N = 10 and C = 10 nF. . . . . 133

8.6 Scheme used for obtaining the final signal (Vout). The designed

source for the strobe signal, the antenna for the fixed systems,

and the human body model has been taken into account. . . . 134

8.7 Lung volume in function of the time. . . . . . . . . . . . . . . 135

8.8 Output voltage as a function of the volume (N = 100). . . . . 136

8.9 Signal related to the voltage signal. . . . . . . . . . . . . . . . 136

8.10 Receiver schematic layout. . . . . . . . . . . . . . . . . . . . . 137

8.11 Receiver 3D layout. . . . . . . . . . . . . . . . . . . . . . . . . 138

viii

List of Tables

1.1 FCC emission limits (EIRP in dBm/MHz ) for the various

types of UWB systems. . . . . . . . . . . . . . . . . . . . . . . 22

1.2 EC decision on maximum mean and peak EIRP. . . . . . . . . 24

3.1 UWB radar systems using range gating receiver. . . . . . . . . 49

3.2 UWB radar systems using correlation detection. . . . . . . . . 49

3.3 Assembled UWB radar systems. . . . . . . . . . . . . . . . . . 50

7.1 Simulated fidelity of the proposed antenna. . . . . . . . . . . . 120

8.1 Output voltage values obtained varying the amplitude of the

input voltage. The strobe signal arrives in phase with the

received signal. . . . . . . . . . . . . . . . . . . . . . . . . . . 130

8.2 Output voltage values obtained varying the time delay of the

input voltage (N = 100). . . . . . . . . . . . . . . . . . . . . . 131

8.3 Simulated output voltage values obtained with the complete

circuit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

ix

Acknowledgment

I wish to thank the many people who have collaborated with me and con-

tributed to various parts of this research. Special thanks go to my advisor

Prof. Stefano Pisa for his help and constant support throughout these three

years. He gave me the chance to face a very interesting and challenging

research topic. I appreciate his vast knowledge and skill in many areas. I

would like to thank Dr. Marta Cavagnaro and Dr. Emanuele Piuzzi for

their support and suggestions. I would also like to thank Prof. Mohammad

Ghavami, Dr. Panagiotis Kosmas, and Dr. Reza Dilmaghani for support-

ing this research during my visiting scholarship at King’s College London.

I would like to express my gratitude to my family for supporting and en-

couraging me during this exciting adventure. Many thanks to Paolo for his

sincere friendship. The biggest thank goes to Domenico.

xi

Introduction

Continuous monitoring of cardio-respiratory activity is crucial for the diag-

nosis of many respiratory apparatus pathologies and for the vital monitoring

during hospital confinement or home therapy [1]. The analysis of the breath

rate is useful in evaluating pathologies of the breath activity and in pre-

venting diseases such as the sudden infant death syndrome (SIDS) and the

obstructive sleep apnoea (OSA), while the analysis of the cardiac activity can

assess pathologies of the cardiac apparatus and carry out diagnosis based on

the history of the cardiac signal.

Nowadays breath activity monitoring is usually conducted by spirometric

apparatuses (see Fig. 1(a)), by inductive bandage systems placed around

the thorax, or by airtight jackets [1], while cardiac activity monitoring is

typically performed through electrocardiograph (ECG) (see Fig. 1(b)).

Such conventional techniques are well known and consolidated, but in

some situations are particularly uncomfortable or not applicable to the pa-

tients. Indeed, they require an active involvement for the subject (e.g.,

spirometry), electrodes in contact with the skin (e.g., ECG) and, further-

more, the monitoring is possible only for a short period of time.

By using the electromagnetic radiation in the microwave region, it is po-

tentially possible to monitor any physiological activity involving movements

of parts of the body without contact with the subject under observation,

and, therefore, to carry out a remote monitoring in a non-invasive way [2].

The systems proposed in literature for the remote monitoring of cardio-

respiratory activity are mainly based on Doppler [3, 4] or ultra wideband

(UWB) [5, 6] techniques.

Doppler radars have been used for monitoring moving targets since the

1

Figure 1: Cardio-respiratory monitoring conventional techniques: spirometry(a), ECG (b).

early 1970s [7]. The Doppler radars were developed by using heavy and ex-

pensive components, thus limiting their use to research environments. How-

ever, recent advances in wireless technology enabling integration of Doppler

radar on a single chip have made them compact and light.

Doppler radar systems transmit a continuous wave (CW) electromagnetic

signal that is reflected from a target and then demodulated by the receiver.

According to the Doppler theory [8], a target with a time varying position

reflects the signal modulating its phase proportionally to the time-varying

position of the target. In the case of breath and beat monitoring, since the

chest has periodic movements, the radar will receive a signal similar to the

transmitted one, with a phase that is modulated by the time varying chest

position.

UWB radars are today a valuable alternative with respect to the Doppler

radar. In a UWB radar system, the transmitter generates a sequence of short

pulses with duration of the order of hundreds of picoseconds. These pulses

excite the antenna and are radiated in space; then, the pulses are reflected

by the subject. The reflected field arrives to the same or another antenna

2

Figure 2: Remote sensing of human vital signs.

and, if the target moves, the system is able to detect this movement from

the changing in the arrival time of the received signal.

The main advantages of UWB methodology are:

low power spectral density level, associated with the transmission of ul-

tra short impulses, and the low interference with other wireless systems

present in the environment;

great discrimination range, i.e., the ability of detecting objects located

few centimetres away from the transmitting antenna;

great resolution that allows to measure independently both the thorax

and heart movements.

Other useful characteristics of UWB technology are the low costs, since

such radars may be entirely realized using hybrid technology surface mounted

components; the great immunity to unwanted echoes - in particular, when

the range gating reception technique with pseudo-random impulse generation

is used [9]; the considerable increase in receiver sensitivity if range gating

technique is used.

3

Furthermore, since the energy density of the radiated signals has a very

large spectrum with levels near those of environmental noise, UWB radars

can be conveniently used in complex environments where interference with

other apparatus sensible to the electromagnetic radiation can represent a

problem [10]. Finally, on the basis of the present knowledge, the low radiated

power density is not harmful for the patient health [2, 11].

The first UWB radar for remote monitoring, resulting from the work

carried out at the Lawrence Livermore National Laboratory (LLNL), has

been invented and patented in 1994 [12]. Successively, other studies have

been performed [2, 13, 14, 15, 16] and experimental UWB radar prototypes

have been built and tested.

Other medical applications are the monitoring of pregnant and the mon-

itoring of internal blood pressure, that can be indirectly derived from a mea-

surement of arterial pulsation, and, in general, any object of adequate size

can be monitored (e.g., vocal cords, vessels, bowels, lung, chest, bladder,

fetus, etc.) [11].

UWB radars can also be used in urban-warfare, counter-terrorism, calamity

rescue scenarios [17], and for the monitoring of the astronauts during their

space flight. Recently, the Italian Space Agency (ASI) has approved the

pioneer project NIMURRA concerning the non invasive monitoring by ul-

tra wideband (UWB) radar of respiratory activity of people inside a spatial

environment. The Department of Information Engineering, Electronics and

Telecommunications (DIET), where my thesis work has been developed, is

one of the participant of this project.

Motivation

Many motivations are behind this thesis. Although conventional techniques

for the cardio-respiratory activity monitoring are now consolidate, using a

remote technique leads to a series of advantages. Indeed, non contact sensors

allow for a continuous monitoring without confining the subject with cables,

and avoid the use of electrodes or straps that are very uncomfortable.

The UWB systems proposed in literature have been assembled using com-

4

mercially available subsystems without an ad-hoc design for the specific ap-

plication. For this reason, in this thesis, the study of a model of the UWB

radar system, including the source, the receiver, the transceiver antenna, the

transmission medium, and the human body interaction is faced.

Moreover, instead of using expensive sampling oscilloscopes and commer-

cial sources and antennas, hybrid circuits on planar substrates represents a

valid alternative for the realization of the various system blocks.

Outline

The main topic of this thesis is the remote cardio-respiratory activity mon-

itoring by using UWB radar systems. In addition to the description and

classification of the systems proposed in literature, novel approaches and

solutions are provided.

The thesis is organized as follows. Part I first presents UWB radar histor-

ical background and the related regulations (Chapter 1), then the main fea-

tures (Chapter 2) and the analysis of the state-of-the art of the UWB systems

for the cardio-respiratory monitoring (Chapter 3), providing an overview of

the problem and a classification of the methods proposed in literature.

Part II concerns the formulation of a complete model of the radar, which

takes into account the signal source, the transceiver antenna properties, and

the radar cross section of the target (Chapter 4). The circuit model is

validated both numerically (Section 4.2) and experimentally (Section 4.3).

Chapter 5 shows the feasibility study of UWB radars for breath activity

monitoring. In particular, an anatomical model of the human body, based

on the visible human (VH), is used to compute the corresponding radar cross

section (Section 5.2).

Part III reports the study and design of each component. In particular,

various kind of UWB sources are presented with their realization and mea-

surement results (Chapter 6), two novel UWB antennas are designed and

measured (Chapter 7), and different UWB receiver schemes are discussed

and optimized for the specific application (Chapter 8).

Finally, conclusions, future directions, and open issues are discussed.

5

Contributions

The main contributions of this thesis are:

1. a complete circuit model of a UWB radar system that allows to:

(a) design the system components;

(b) study the system signal time behaviours;

(c) carry out compliance tests of the radiated field;

2. the design and realization of UWB sources;

3. the design and realization of two novel UWB antennas;

4. a target model that takes into account the complex value of the human

body radar cross section;

5. two new models of the human body representing different stages of the

respiratory activity;

6. the study and design of UWB receivers.

Publications

Part of this thesis has been published in International Journals, National and

International Conference Proceedings:

E. Pittella, S. Pisa, P. Bernardi, M. Cavagnaro and E. Piuzzi, “Breath

Activity Monitoring by Using an ad-hoc Designed UWB Radar”, ac-

cepted for publication, EBEA 2011.

S. Pisa, P. Bernardi, M. Cavagnaro, E. Pittella, and E. Piuzzi, “A

Circuit Model of an Ultra Wideband Impulse Radar System for Breath

Activity Monitoring”, submitted to a Journal.

E. Pittella, P. Bernardi, M. Cavagnaro, S. Pisa, E. Piuzzi, “Design of

UWB antennas to monitor cardiac activity”, accepted for publication

in ACES Journal.

6

E. Pittella, P. Bernardi, M. Cavagnaro, S. Pisa, E. Piuzzi, “Mod-

elling of a Ultra Wideband Radar System for Breath Activity Mon-

itoring”, XVIII Riunione Nazionale di Elettromagnetismo, Benevento,

Italy, September 2010.

E. Pittella, P. Bernardi, M. Cavagnaro, S. Pisa, and E. Piuzzi, “Design

of an UWB antenna to monitor cardiac activity”, In Proceedings of the

26th Annual Review of Progress in Applied Computational Electromag-

netics, Tampere, Finland, pp. 564−568, April 2010.

P. Bernardi, M. Cavagnaro, S. Pisa, E. Pittella, E. Piuzzi. “ Ultra

Wideband Radar System for Breath Activity Monitoring”, Attivita di

Ricerca del Centro Interuniversitario ICEmB a Venti Anni dalla Sua

Costituzione, Genova, pp. 51−52, February 2010.

E. Pittella, P. Bernardi, M. Cavagnaro, S. Pisa, E. Piuzzi. “ Numerical

and Experimental Validation of a Circuital Model of a UWB Radar

for the Breath Activity Monitoring”, Abstract Collection of BIOEM

2009 Davos (Joint Meeting of the Bioelectromagnetics Society and the

European BioElectromagnetics Association), Davos, Switzerland, paper

P−217, June 2009.

S. Pisa, P. Bernardi, M. Cavagnaro, E. Pittella, E. Piuzzi. “ Un modello

circuitale per lo studio di fattibilita di un radar UWB applicato al

monitoraggio dell’attivita respiratoria”, XVII Riunione Nazionale di

Elettromagnetismo, Lecce, Italy, paper no. 49, September 2008.

S. Pisa, P. Bernardi, M. Cavagnaro, E. Pittella, E. Piuzzi. “ Moni-

toring of Cardio-Pulmonary Activity With UWB Radar: A Circuital

Model”, Proceedings of 19th International Zurich Symposium on Elec-

tromagnetic Compatibility, Singapore, pp. 224−227, May 2008.

7

Collaborations

The work presented in this thesis has been carried out in collaboration with

other people. In particular, during my visiting scholarship at King’s Col-

lege London, I collaborated with Prof. Mohammmad Ghavami, Head of the

UWB Communications Group, Dr. Panagiotis Kosmas, and Dr. Reza Shams

Dilmaghani, lecturers with the same group. During all my Ph.D. course, I

collaborated with the Microwave Lab Group, Department of Information

Engineering, Electronics and Telecommunications (DIET).

8

Part I

Ultra Wideband Radar Systems

9

Chapter 1

Introduction to UWB

Radio and Radar Systems

The acronym UWB stands for “ultra wideband” and refers to signals or sys-

tems that have a large fractional or absolute bandwidth. UWB is commonly

referred to electromagnetic waveforms with an instantaneous fractional band-

width greater than about 0.20-0.25 [18]. Such a large bandwidth provides

peculiar advantages with respect to narrowband systems in terms of signal

robustness and information content, but lead to fundamental differences from

traditional systems [10].

The majority of conventional radio systems use a narrowband signal mod-

ulating a sinusoidal carrier, because a sine wave is very simple to generate

from the oscillation of an LC circuit, which in turn is the most elementary

and widespread oscillatory system.

However, narrowband signals have small information capability, since the

amount of the information transmitted in a unit of time is proportional to

the band. Sometimes, increasing the transmitting time can be infeasible, for

example when the operational time is limited: in this case, the transition to

ultra wide bandwidth signals seems to be very promising [19].

UWB systems transmit short duration impulses, thus offering several ad-

vantages with respect to narrowband communications systems [20]:

1. improved detected target range measurement accuracy, that results in

11

the improvement of the radar resolution for all coordinates;

2. coexistence with current narrowband and wideband radio services with

the benefit of avoiding expensive licensing fees;

3. large channel capacity, that can support real-time high-definition video

streaming;

4. ability to work with low SNRs offering high performance in noisy en-

vironments;

5. low transmit power, which provides high degree of security with low

probability of detection and interception;

6. resistance to jamming1, that makes the system reliable in hostile envi-

ronments;

7. high performance in multipath channels delivering higher signal strengths

in adverse conditions;

8. simple transceiver architecture enabling ultra-low power and lower pro-

duction costs;

9. decrease of the radar dead zone.

All of the above mentioned reasons make the UWB technology a successful

solution for a series of useful applications [20].

In the remainder of this Chapter, a short historical background of the

UWB radio and radar systems (Section 1.1) and the current regulatory sit-

uation (Section 1.2) are provided.

1Radio “jamming” is a usually deliberate transmission of radio signals that disruptcommunications by decreasing the signal to noise ratio. Originally the terms “jamming”and “interference” were used interchangeably but nowadays most radio users use the term“jamming” to describe the deliberate use of radio noise or signals in an attempt to disruptcommunications whereas the term “interference” is used to describe unintentional formsof disruption.

12

1.1 Historical Background

UWB systems has received great attention at the beginning of the XXI cen-

tury, even if UWB origins date back more than a century.

Indeed, at the end of the XIX century, the easiest way to generate an

electromagnetic signal was to use a spark-gap 2. The radio history shows

that the spark gap transmitter was the result of the work of many people.

In 1862, James Clerk Maxwell formulated his famous equations, setting the

basis of computational electromagnetics, predicting the propagation of elec-

tromagnetic waves [21]. In 1887, David Edward Hughes used a spark gap

to generate radio signals, achieving a detectable range of approximately 500

meters. Successively, in 1888, physicist Heinrich Hertz verified Maxwell’s pre-

dictions. Hertz used a tuned spark gap transmitter and a tuned spark gap

detector, consisting of a loop of wire connected to a small spark gap, located

a few meters away (Fig. 1.1(a)). Through a series of experiments, Hertz

verified that electromagnetic waves were being produced by the transmitter;

indeed, when the transmitter sparked, small sparks also appeared across the

receiver’s spark gap, which could be seen under a microscope.

In 1893, Nikola Tesla introduced his radio system and later developed a

primary tuning device, the loose coupler, used in the early receivers; more-

over, Tesla took out a first patent [22] on a reliably device to produce radio

frequencies (see Fig. 1.1(b)).

According to the generally accepted criterion, Guglielmo Marconi is con-

sidered to be the inventor of an early form of radiotelegraphy. Marconi began

experimenting with wireless telegraphy in the early 1890s. In 1895, he suc-

ceeded in transmitting over a distance of 1.25 miles (about 2 kilometers).

His first transmitter was made of an induction coil connected between a wire

antenna and the ground, with a spark gap across it. Every time the in-

duction coil pulsed, the antenna would be momentarily charged up to tens

(sometimes hundreds) of thousands of volts until the spark gap started to

arc over. This acted as a switch, essentially connecting the charged antenna

2A spark gap consists of an arrangement of two conducting electrodes separated by agap usually filled with a gas such as air, designed to allow an electric spark between theconductors.

13

Figure 1.1: (a) Scheme of Hertz experimental set-up ; (b) Nikola Tesla’sspark-gap transmitter.

to ground, producing a very brief burst of electromagnetic radiation [21, 23].

The first experiments with wireless telephony have been conducted by

Reginald Aubrey Fessenden and later by Lee De Forest [21]. In Decem-

ber 1900, Fessenden used impulse radio signals for transmitting speech over

one mile. As well as practical experiment, also theoretical research into the

propagation of impulse radiation originated in that period: as an example,

the great theoretician Arnold J.W. Sommerfeld, was the first to analyze the

diffraction of a short pulse by a half plane, a fundamental problem of UWB

propagation [24].

However, at the beginning of the XX century, the general interest ad-

dressed to narrowband communications that offered an easy way of trans-

mitting multiple signals in a finite bandwidth through frequency division

multiplexing, while it was not known how to exploit the spark-gap signal.

The interest in wideband communications reappeared in the 1960s in the

military radar context, where spectral efficiency was not the major problem.

In such a context, the crucial point was to improve the spatial resolution, i.e.

the accuracy in determining the roundtrip from the radar transmitter to a

14

target. It can be determined the better way, the shorter the transmitted radar

pulses are. Increased interest in these systems concurred with the invention

of the sampling oscilloscopes, which allowed the experimental analysis of

short-duration signals in the time domain.

A first patent for an early impulse system was obtained by Louis A. De

Rosa [25]; in another patent, awarded to Conrad H. Hoeppner [26], a repre-

sentation of a pulsed communication system was presented. Main advances

in UWB systems were obtained in the first 1970’s with the pioneering work of

Henning F. Harmuth at Catholic University of America [27, 28, 29], Gerald

F. Ross and Kenneth W. Robbins at Sperry Rand Corporation [30, 31, 32],

and Paul van Etten at the USAF’s Rome Air Development Center [33] and

in Russia [34, 35].

Harmuth gave the basic design for UWB transmitters and receivers in

[36, 28, 37, 38]. Ross and Robbins’ patents introduced the use of UWB

signals in many application areas. The patent [31] by Ross is a stronghold

patent in UWB technology. Van Etten’s empirical testing of UWB radar

systems resulted in the development of system design and antenna concepts

[27].

As regards Russian systems, the theoretical basis for time-scale trans-

formation procedures given in [34] allowed the development of the 10 GHz

sampling oscilloscopes. Investigations that led to the formulation of a time

domain analysis of signals or radar target characteristics involving target im-

pulse response as well as signal shape and signal structure description have

been conducted in [35, 39].

A UWB system for ground penetrating radar (GPR) was presented in [40],

which contributed to new developments in UWB field, while other subsurface

UWB radar systems were presented in [41].

In the same period, there were new developments of sample and hold

receivers at Tektronix Inc. For example, in [42], a Time Domain Receiver

is presented utilizing a technique which enabled UWB signal averaging; in

fact, the sampling circuit is a gate followed by an integrator. The Hewlett

Packard Company also contributed to UWB improvement with a step for-

ward in the sampling oscilloscope. In those years, both Hewlett Packard

15

and Tektronix produced the first time domain instruments for diagnostics

[27]. At the Lawrence Livermore National Laboratory (LLNL) and at the

Los Alamos National Laboratory (LANL) original research on pulse trans-

mitters, receivers, and antennas have been also performed.

Since 1978, there have been numerous sessions at various conferences,

where many approaches to UWB pulse generation have been discussed.

During the 1980s, the United States Air Force (USAF) developed a pro-

gram in UWB system led by J.D. Taylor. Taylor was able to organize a UWB

workshop for the US Department of Defense’s attended by over 100 partic-

ipants [43]. At this time, there was progress in UWB not only in the US

but also in Russia and China. There were also academic programs (e.g., at

LLNL, LANL, University of Michigan, University of Rochester and Polytech-

nic University, Brooklyn) which focused on the interesting physics of short

pulse transmissions that differed from the physics of continuous or long pulse

signals, especially with respect to interactions with the matter [27].

In 1994, T.E. McEwan, at LLNL, invented the Micropower Impulse Radar

(MIR), a compact and cheap UWB radar operating at ultralow power [12].

It was the first UWB radar able to operate with few microwatts of battery

drain. The methods of reception of this design also permitted, for the first

time, extremely sensitive signal detection.

An obstacle to the commercial use of UWB was the problem of frequency

band regulations. Frequency regulators all over the world assign narrow

frequency bands to specific services and operators. UWB systems emit ra-

diation over a large frequency range, including the bands already assigned

to other services. Only in 2002, the Federal Communications Commission

(FCC) issued a first report that allowed intentional UWB emissions in the

frequency range between 3.1 and 10.6 GHz, with certain restrictions for the

emission power spectrum [18] (see Sec. 1.2).

After the first FCC report, many companies were working on the topic.

The Institute of Electric and Electronics Engineers (IEEE) established a

working group (IEEE 802.15.3a) with the task of standardizing a physical

layer for high throughput wireless communications based on UWB [20].

UWB is also beneficial for the transmission of data with low rates, using

16

as little energy as possible. Since the goals are greatly different from the high-

data rate applications, a different standardisation group was commissioned

for such devices, i.e. the IEEE 802.15.4a group.

In summary, the pioneering papers of Harmuth, Ross, Robbins, van Etten,

and Morey, as well as extensive work carried out in Russia, have defined

UWB radar systems, during the 1970s and 1980s. After their contributions,

the only significant improvements in UWB field were the new developments

of the sample and hold oscilloscope and the original work carried out by

Azevedo and McEwan at LNLL [12, 5, 6].

1.2 Regulations

Since UWB systems use very large bandwidth, interferences may occur with

other users and with the existing communication systems. Therefore, regula-

tions of the radio spectrum are necessary to harmonize the frequency use by

many wireless services. In the reminder of this Section the normative issued

by regulatory bodies in several countries are presented.

1.2.1 United States Regulations

In USA, spectrum jurisdiction is split between the Federal Communications

Commission (FCC) and the National Telecommunications and Information

Administration (NTIA) [44]. While FCC is an independent agency regulating

private users, states, and local governments, NTIA acts on behalf of the

President and regulates Federal Government users. Frequency bands are

controlled by FCC, or controlled by NTIA, or shared and subject to mutual

agreement. As regarding UWB issues, both agencies are involved and mutual

agreement is needed.

A first report in order to verify the possibility for UWB systems to coexist

with other existing systems was performed by NTIA [45]. Several measure-

ment campaigns were carried out in the United States and then a first report

on the assessment of compatibility between UWB systems and selected Fed-

eral systems was released by NTIA in January 2001 [46]. A second report on

17

the assessment of compatibility between UWB systems and GPS receivers

was released on February 2001 [47].

A milestone in the history of UWB was set in 2002, when the FCC ap-

proved the first guideline (see Fig. 1.2) allowing the intentional emission of

UWB signals and specified emission masks [18] .

Figure 1.2: FCC first guidelines on UWB technology.

In the FCC document, UWB is presented as a technology with enormous

potentials. The same report highlights the need for emission masks, due to

the unknown effects that UWB transmissions may have on other communi-

cation systems.

According to FCC, the UWB bandwidth is bounded by the points 10 dB

below the highest radiated emission, as obtained by the complete system,

including the antenna. The upper boundary is designated fH and the lower

boundary is designated fL. The frequency at which the highest radiated

emission occurs is designated fM . The center frequency, is given by:

fC =fH + fL

2(1.1)

while the fractional bandwidth is equal to:

FB =2(fH − fL)

fH + fL(1.2)

Any signal is considered by FCC as UWB if, at any point in time, it has

a central frequency lower than 2.5 GHz and it has a fractional bandwidth

18

equal to or greater than 0.20 or it has a bandwidth equal to or greater than

500 MHz, regardless of the fractional bandwidth.

In the First Report and Order (R&O) [18] FCC established different

technical standards and operating restrictions for three types of UWB devices

based on their potential interference with other device:

Imaging systems (ground penetrating radar, wall and through-wall

surveillance, medical systems)

Vehicular radar systems

Communication and measurement systems

Imaging systems do not include systems designed to locate tags or sys-

tems used to transfer voice or data information. Imaging systems comprise:

1. Ground penetrating radar (GPR) is a field sensor system designed to

operate only when in contact with, or within one meter from, the

ground for the purpose of detecting buried objects or determining the

physical properties of the ground. For this purpose, the energy radi-

ated by the GPR is intentionally directed down into the ground. These

systems must operate with a UWB bandwidth below 10.6 GHz. Us-

age must be licensed and is limited to public safety, scientific research,

commercial mining or construction.

2. Medical imaging systems are designed to detect a target or movements

within the body of a person or animal. UWB medical imaging systems

must have a bandwidth contained between 3.1 and 10.6 GHz. They

may only be operated by, or under supervision of, a licensed health

care practitioner.

3. Wall imaging systems aim to detect objects contained within a “wall” or

to determine its physical properties. The “wall” is a concrete structure,

the side of a bridge, the wall of a mine or another physical structure

that is dense and thick enough to absorb the majority of the signal

transmitted by the imaging system. This category of equipment does

19

not include products such as “stud locators” that are designed to locate

objects behind gypsum, plaster or similar walls that are not capable of

absorbing the transmitted signal.

4. Through-wall imaging systems concern the detection of objects, people,

or movements on the other side of an opaque structure such as a wall

or a ceiling. This category of equipment may include products such

as “stud locators” that are designed to locate objects behind gypsum,

plaster or similar walls that are not thick enough or dense enough to

absorb the transmitted signal. The use of through-wall imaging systems

is limited to state or local public safety organizations, and must be

licensed. There are two types of through-wall imaging systems: those

with a bandwidth below 960 MHz, and those with fC and fM contained

within 1.99 to 10.6 GHz.

5. Surveillance systems are used to establish a permanent RF field that

is used for security purposes to detect the intrusion of persons or ob-

jects. The UWB bandwidth of these systems must be between 1.99 and

10.6 GHz. Operation must be licensed and is limited to public safety,

manufacturers, petroleum and power licensees.

Vehicular radar systems are devices able to detect the presence and

movement of objects near a vehicle, enabling features such as near collision

avoidance, improved airbag activation, and suspension systems that better

respond to road conditions. These systems must operate only when the

engine is running, and must have a specific activation such as engine starting,

turn signal activation, etc. UWB bandwidth must be within 22 and 29 GHz

and fC must be higher than 24.075 GHz. Above 30 degrees elevation, signals

at 23.6-24.0 GHz must be 25 dB lower than the listed limits, increasing to

35 dB at 30 degrees after 1 January 2014.

Communication and measurement systems must operate in the 3.1-

10.6 GHz frequency band. The equipment must be designed to ensure that

operation can only occur indoors or it must consist of hand held devices that

may be employed for such activities as peer-to-peer operation.

20

Figure 1.3: FCC indoor (a) and outdoor (b) emission mask.

Tab. 1.1 lists the FCC emission limits for the various types of UWB

systems, while in Fig. 1.3 the FCC regulations about UWB emissions, in

terms of equivalent isotropically radiated power (EIRP), are reported.

The EIRP is the product of the power supplied to the antenna and the

antenna gain in a given direction relative to an isotropic antenna. The EIRP,

in terms of dBm, can be converted to a field strength, in dBµV/m at 3 meters,

by adding 95.2 [48].

The FCC indoor and outdoor emission limit difference is due to the fact

that outdoor UWB systems could interfere, for example, with aeronautical

radar systems while indoor UWB systems would, in most cases, have signals

attenuated by building and walls before they reach radar receivers. For this

reason, for indoor systems a higher limit is allowed.

Indoor system equipment must be designed to ensure that operation can

only occur indoors or it must consist of hand-held devices that may be em-

ployed for activities as peer-to-peer operation, i.e., may transmit only when

sending information to an associated receiver and emission should not be

intentionally directed outside of the building in which the equipment is lo-

cated.

21

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22

For hand-held devices, the indoor or outdoor use is permitted, the -10 dB

bandwidth must be between 3.1-10.6 GHz and the device may transmit only

when sending information to an associated receiver.

In Paragraph 1 of the First Report and Order, FCC states that: “We are

concerned, however, that the standards we are adopting may be overprotec-

tive and could unnecessarily constrain the development of UWB technology.

Accordingly, within the next six to twelve months we intend to review the

standards for UWB devices and issue a further rule making to explore more

flexible technical standards and to address the operation of additional types

of UWB operations and technology”.

In March 2003, FCC published a Memorandum Opinion and Order and

Further Notice of Proposed Rulemaking [49], where several changes were

made mainly for clarification. This Memorandum amends Part 15 in re-

sponse to 14 petitions filed after the original Report and Order on UWB.

While not making major changes in the technical operating parameters for

UWB devices, it does relax restrictions on operations of through wall imaging

systems and ground penetrating radar. New rules are proposed to address

issues raised regarding the definition of a UWB device, the operation of low

pulse repetition frequency UWB systems, including vehicular radars, in the

3.1-10.6 GHz band, the operation of frequency hopping vehicular radars in

the 22-29 GHz band as UWB devices, and the establishment of new peak

power limits for wideband Part 15 devices that do not operate as UWB

devices.

Actual rules are mostly the same of the First Report and Order with the

above mentioned changes.

1.2.2 European Regulations

The regulatory bodies involved in the regulations of UWB in European coun-

tries are the European Technical Standard Institute (ETSI) and the Euro-

pean Conference of Postal and Telecommunications Administration (CEPT).

The European Union asked ETSI for an harmonized UWB standard. After

the studies conducted by CEPT, in 2004 ETSI established a working group

23

on Electromagnetic compatibility and Radio spectrum Matters (ERM) in or-

der to develop an harmonized standard for UWB device operating in a short

range. This group comprised both the task group ERM TG31A for generic

UWB and the the task group ERM TG31B for automotive higher frequency

band applications [50].

ETSI standardization activity for short-range devices currently includes

UWB communications applications, ground-probing and wall-probing radar,

tank level probing radar, sensors, precision location within buildings, au-

tomotive radar. In 2003, the European Commission appointed CEPT to

conduct the technical work for the introduction of UWB technology in Eu-

rope. In March 2006, the Electronic Communications Committee (ECC)

issued rules for UWB considering the proposed technical recommendations

and gave a first approval for the 6-8.5 GHz band with an EIRP emission level

of -41.3 dBm/MHz [51].

Successively, ETSI, in close cooperation with ECC, issued an harmonized

standard, EN 302 065 [52], including specific new definitions, methods of

measurements, and limits required for Ultra Wide Band (UWB) technology.

In April 2009, the EC decision on the armonization of the radio spectrum

for UWB technology has been published [53]. Tab. 1.2 reports the maximum

Frequency Max. mean EIRP Max. peak EIRP(GHz ) (dBm/MHz ) (dBm/50 MHz )

f ≤ 1.6 -90.0 -50.01.6 < f ≤ 2.7 -85.0 -45.02.7 < f ≤ 3.4 -70.0 -36.03.4 < f ≤ 3.8 -80.0 -40.03.8 < f ≤ 4.2 -70.0 -30.0

4.2 < f ≤ 4.8

-41.3 0.0(until Dec. 31st 2010) (until Dec. 31st 2010)

-70.3 -30.0(beyond Dec. 31st 2010) (beyond Dec. 31st 2010)

4.8 < f ≤ 6.0 -70.0 -30.06.0 < f ≤ 8.5 -41.3 0.08.5 < f ≤ 10.6 -65.0 -25.0

f > 10.6 -85.0 -45.0

Table 1.2: EC decision on maximum mean and peak EIRP.

24

mean and peak EIRP for equipment using ultra wideband technology.

The limits for indoor UWB communication are shown in Fig. 1.4. The

maximum EIRP levels of the CEPT and FCC masks are identical; however,

the skirts of these masks are different as can be note comparing Fig. 1.4 and

Fig. 1.3.

Figure 1.4: Emission limits issued by EC in 2009.

1.2.3 Japanese Regulations

Japanese regulations allocate UWB frequency bands from 3.4 to 4.8 GHz

and from 7.25 to 10.25 GHz. The average transmission power is limited to

-41.3 dBm/MHz in both bands. Japanese emission mask is depicted in Fig.

1.5.

In August 2006 an official of Japan’s Ministry of Internal Affairs and

Communications declared: “First, we will promote discussions to define the

interference reduction technology. Then, we will discuss approval of sensor

applications, for example, distance measurement. Although the latest an-

nouncement was limited to the approval of indoor usage, outdoor usage must

also be discussed. In addition, we plan to set up a working group to discuss

regulations on the 24 GHz band for use in automotive radars”.

25

Figure 1.5: Proposed UWB japanese mask.

26

Chapter 2

UWB Radars

RADAR is an acronym of “RAdio Detection And Ranging” coined in 1940

by the U.S. Navy [20].

According to [54], radar system is an object-detection system that uses

electromagnetic waves, specifically radio waves, to identify the range, alti-

tude, direction, or speed of both moving and fixed objects such as aircraft,

ships, spacecraft, guided missiles, motor vehicles, etc.

Conventional radars are mainly pulse or continuous wave radars. The

pulse radar is the more conventional one, which transmits a burst of energy

and then waits for the echo reflected back to the antenna. After a specific

period of time (depending on the radar range) another pulse is sent. Since

radar waves travel at the speed of light, range from the returned pulse can

be calculated.

Continuous wave (CW) radars transmit a constant beam of radar energy.

When a CW radar illuminates a moving object (such as an aircraft or a car),

the radar wave returns to the antenna with a frequency that is slightly higher

(if the object is moving toward the radar) or lower than the frequency of the

original radar energy, if the object is moving away from the radar.

A Doppler radar is a specialized radar based on the Doppler effect, ac-

cording to which the frequency of the reflected pulse depends on the target

speed. Thus, it is able to obtain information both on the target position and

motion by sending a microwave signal towards a desired target, waiting for

27

its reflection, and then analyzing how the frequency of the returned signal

has been altered by the object motion [55].

UWB radar systems transmit signals across a much wider frequency than

conventional radar systems. To have an idea, while a conventional radar is

characterized by a fractional bandwidth (FB), given by Eq. 1.2, that is at

most 20% of the center frequency, i.e., 0.01 ≤ FB < 0.20, a UWB radar is

characterized by 0.20 ≤ FB < 1 [56].

An UWB radar works in the time domain; it sends a short impulse and

receives its echo. The distance between the target and the radar can be

estimated by the time of receipt of the echo. By computing the Fourier

transform of a Gaussian pulse it is possible to note how the frequency content

of such a signal is broad: the shorter the time length of the signal, the wider

the bandwidth. This increase in bandwidth actually allows the UWB radar

system to obtain more information about the target; however, each pulse

contains very little information, so it is normal to average pulses sequentially.

2.1 UWB Radar Scheme

Fig. 2.1 shows the basic principle of a UWB impulse radar based on the

range gating principle.

The transmitter emits rapid, wideband pulses towards a target with a

certain repetition rate. This rate is randomized by a noise circuit. The

target distance is supposed to be known a priori. The transmitted pulse is

sent also to a delay line, thus the voltage is read only in a predetermined

time instant. If the echo is received during this pre-established time instant,

the target is in the selected range. The receiver, which uses a pulse-detector

circuit, only accepts echoes from objects within a preset distance (round-trip

delay time) from a few centimetres to many tens of meters [5].

28

Figure 2.1: Basic scheme of an impulse radar.

2.2 UWB Radar Features

The main features of an UWB radar concern the repetition rate, the range,

the resolution, and the accuracy.

These features are detailed in the following.

2.2.1 Repetition Rate

The time between the beginning of one pulse and the beginning of the next

one is called pulse repetition time (∆T) and is equal to the reciprocal of the

pulse repetition rate (RR):

∆T =1

RR(2.1)

29

The RR of the radar system is the number of pulses that are transmitted

per second and influences the maximum range that can be detected.

2.2.2 Range

The target distance can be computed by the round trip delay of the trans-

mitted signal and the speed of light c0.

While the radar slant range Rsr is the line of sight distance between the

radar and the target, the radar ground range Rgr is the horizontal distance

between the transmitter and the target and requires the knowledge of the

target elevation (see Fig. 2.2).

As regards to the slant range, since the wave travels from the transmitter

to the target and then comes back, the round trip time, i.e., the time taken

by the signal to travel to the target and to came back, has to be divided by

two in order to obtain the time the wave spent to reach the target, therefore:

Rsr =tdelayc0

2(2.2)

where Rsr is the slant range, tdelay is the round trip time and c0 is the speed

of light, equal to 3×108 m/s. Thus, the distance between the radar and the

target can be calculated using Eq. 2.2.

Maximum Unambiguous Range

The determination of the unambiguous range is one of the aspects to be

considered in pulse radars. Indeed, the pulsed radar usually transmits a

sequence of pulses, while the receiver measures the time between the leading

edges of the last transmitting pulse and the echo pulse. If an echo is received

from a long range target after the transmission of a second transmitting pulse,

the radar determines a wrong range because the measurement process relates

that pulse with the second transmitted pulse, thus assuming a reduced range

for the target.

The range ambiguity takes place when there are strong targets at a range

in excess of the pulse repetition time (∆T). To increase the value of the

30

Figure 2.2: Radar slant range and ground range.

unambiguous range, it is necessary to increase the ∆T, thus reducing the

RR.

Echo signals, arriving after the reception time, are placed either into the

transmit time, where they remain unconsidered since the radar equipment is

not ready to receive during this time, or into the following reception time,

where they lead to measuring failures (ambiguity).

The maximum unambiguous range Ru can be determined by using the

following formula:

Ru =(∆T − τ)c0

2(2.3)

where τ is the time lenght of the received echo impulse.

31

Minimum Detectable Range

Also the minimum detectable range is important to consider. Indeed, when

the leading edge of the received echo is within the transmitting pulse, the

round trip delay can not be detected, i.e., targets at a range equivalent to

the pulse width are not detected. The minimun detectable range Rm is given

by:

Rm =(τ + ttr)c0

2(2.4)

where ttr is the time the receiver does not listen for the echo, during the

transmission, in order to avoid errors.

The UWB Radar Range Equation

In this paragraph the UWB radar range equation is derived. The power

density (Ps) at the target is given by:

Ps =PtGt

4πR2(2.5)

where Pt is the transmitted peak power, R is the antenna-receiver distance

and Gt is the antenna gain:

G =4πAeλ2

(2.6)

Similar to a receiving antenna, a radar target intercepts a portion of the

power, and reflects it in the direction of the radar. The amount of power

reflected toward the radar is determined by the Radar Cross Section (RCS)

of the target.

RCS (σ) is a characteristic of the target that represents its size as seen by

the radar and has the dimensions of an area; however, it is not the same as the

physical area. For a radar target, the power reflected in the radar’s direction

is equivalent to the re-radiation of the power captured by an antenna of area

σ equal to:

σ =PrPs

(2.7)

32

and:

Pr =PtGtσ

4πR2(2.8)

The power received by the radar is obtained by:

Preceived =PtGtσAe

(4πR2)(4πR2)=

PtGtσ

(4πR2)2

Grλ2

4π(2.9)

Thus:

Preceived =PtGtGrλ

2σ

(4π)3R4(2.10)

The radar range equation is simply the radar equation (2.10) rewritten

to solve for maximum range.

The maximum radar range (Rmax) is the maximum distance that allows

to detect the target. It occurs when the received echo signal equals Smin, i.e.

the minimum power that can be received.

Therefore:

Rmax∼=[PtGtGrλ

2σ

(4π)3Smin

] 14

(2.11)

A very important aspect is that, by using UWB signals, the meaning

of the parameters in the range equation changes. In fact, the gain of the

transmitting antenna Gt, the effective cross section of the receiving antenna,

and the effective radar cross section of the target, σ, become dependent on

time and signal parameters.

It is worth noting that a UWB radar features specific energy losses that

can not be found in a narrowband radar. For instance, under the conditions

of short-pulse transmission, losses arise due to the antenna rejection of the

lower frequencies of the signal spectrum and the mismatch of this signal with

the frequency response of an antenna.

33

2.2.3 Resolution

The radar resolution is the ability of the radar to distinguish between targets

that are very close each other, i.e., the ability of the radar to discriminate

between targets with similar ranges.

Radar resolution is usually divided into two categories: range resolution

and angular resolution [57].

The range resolution is the ability of a radar system to distinguish between

two or more targets on the same bearing, but at different ranges. The degree

of range resolution depends on the width of the transmitted pulse, the types

and sizes of the targets, and the efficiency of the receiver and indicator.

Pulse width is an important factor in range resolution because targets must

be separated from each other more than one half pulse length in order to

distinguish between the two. Targets that are too close can appear as one

and can be displayed accordingly (stretched along the beam axis). Since pulse

length is unaffected by distance, the separation criteria is only a function of

the pulse length.

Therefore, the theoretical range resolution of a radar system Sr can be

calculated from the following formula:

Sr =c0τ

2(2.12)

where c0 is the speed of light and τ is the transmitted pulse width.

Angular resolution is the minimum angular separation at which two equal

targets at the same range can be separated. The angular resolution as a dis-

tance between two targets depends on the slant-range and can be calculated

by the following formula:

SA ≤ 2Rsinϑ

2(2.13)

where θ is the antenna beam width and R is the slant range antenna-target.

2.2.4 Accuracy

Accuracy is the degree of compliance between the estimated position or speed

of the target and its true position or velocity.

34

The value of required accuracy represents the uncertainty of the reported

value with respect to the true value and indicates the interval in which the

true value lies with a certain probability. The recommended probability

value is 95%, which corresponds to two standard deviations of the mean for

a normal distribution of the variable.

35

Chapter 3

Breath Activity Monitoring

Systems

In this Chapter, various medical applications of UWB radars are listed (Sec-

tion 3.1), and the state of the art for vital signs monitoring is reported

(Section 3.2).

3.1 Medical Applications of UWB Radars

As detailed in [5, 2, 11] UWB radars are a great promise for a variety of

medical applications, among which:

continuous monitoring of breath activity and diagnostic allowing the

prevention of some syndromes of the respiratory apparatus like the Sud-

den Infant Death Syndrome (SIDS), and the Obstructive Sleep Apnea

Syndrome (OSAS);

remote cardiac monitoring and measurement of the Heart Rate Vari-

ability (HRV);

pregnancy monitoring;

measurement of the cardiac volume;

37

measurement of the internal blood pressure obtained from arterial pul-

sation detection;

monitoring of vocal cords, vessels, bowels, lung, chest, bladder, fetus,

and in general organs of suitable size.

3.2 State of the Art

The idea of monitoring physiologic functions in humans using radars started

as early as the 1970s [58, 59, 60], but the development was limited by the

cumbersome and expensive technology of those years. Furthermore, problems

linked to microwave radiation safety were another deterrent.

With particular reference to UWB technology, chronologically, the first

UWB radar for remote sensing, resulting from the work done by McEwan

at the Lawrence Livermore National Laboratory (LLNL) was invented and

patented in 1994 [12] (Fig. 3.1). In this patent, a compact low-power radar

system was presented, based on a completely new approach to motion sensor

technology. The radar system operates as a pulse-echo system that clocks

the round-trip of a short electrical pulse directly applied to the antenna.

Figure 3.1: Block diagram of the UWB radar motion sensor.

38

The range of the radar is given by the pulse-echo interval and a range

gating receiver is used for the detection of the motion. This kind of receiver

only accepts echoes from objects within a preset distance (round-trip delay

time). It is based on a sampling gate that is opened at a fixed delay after

the transmitted pulse, then the resultant sampling output is averaged over

repeated pulses. In this way, changes in the output stand for motion.

This radar system, presented also in [5], is named Micropower Impulse

Radar (MIR). Unlike conventional radar, which sends out continuous waves

in bursts, MIR uses very short electromagnetic pulses. Furthermore, it can

detect objects at much shorter ranges and is also less expensive with respect

to conventional radars.

The principal MIR components are a transmitter with a pulse generator,

a receiver with a pulse detector, a timing circuitry, a signal processor, and

antennas. The components are shown in Fig. 3.2.

Figure 3.2: MIR radar block scheme.

Possible commercial applications of MIR system can be classified as fol-

lows [5]:

1. Automotive: parking assistance, backup warning, precollision detec-

tion, cruise control, airbag deployment, electronic dipstick for all fluid

39

levels;

2. Security: home intrusion and motion sensor, keyless locks, automatic

doors, child monitoring, vehicle theft alarm, radar trip wire, perimeter

surveillance;

3. Appliances: stud finder, laser tape measure, wireless thermostat, au-

tomatic dispenser, automatic tool shutoff, toys, games, and virtual re-

ality;

4. Manufacturing: fluid-level, proximity, and harsh-environment sens-

ing, robotic sensor, industrial automation.

As regards to medical applications, promising ones, like the remote mon-

itoring of human vital signs (Fig. 3.3) can be found in literature. Further-

more, it is worth noting that the average emission level used is of about a

microwatt, that is about 3 orders of magnitude lower than most interna-

tional standards for continuous human exposure to microwaves making MIR

a medically harmless diagnostic device [5].

Figure 3.3: MIR received signal and conventional electrocardiogram trace.

A first model of the interaction of the UWB signal with the human body

has been studied by Staderini [2] in 2002. In this work, the human thorax

40

was modelled as a dielectric target made of six planar layers (Fig. 3.4), from

the skin to the heart, considering thickness, impedance, linear attenuation,

and wave speed. The model was based on the data obtained from the Visible

Human Project [61] and Gabriel’s measurements of dielectric properties of

tissues [62]. The data allows for the computation of echoes time delay the

linear attenuation and reflection coefficients at boundaries.

Figure 3.4: Staderini human tissues model.

Although it is the first attempt to seriously model the phenomena, the

model remains intrinsically wrong because the dielectric properties used were

those measured on actual living tissues using a continuous wave at 1500 MHz,

while for an effective model ultra wide-band dielectric properties are needed.

This means that a convolution method, or a Finite Differences Time Domain

technique like that already employed in [63] should be used. Another critical

component of the model was the antenna, which should be a non-resonating

one, while in [2] a dipole antenna was used .

41

The use of UWB radar in medicine for the remote sensing of patient’s

cardio-respiratory activity has been also tackled by Immoreev and Samkov

[64] in 2002. A simplified block scheme of the UWB radar system proposed

by Immoreev and Samkov is shown in Fig. 3.5. The description of a non-

contact system and its advantages are reported, and a prototype of the radar

was realized and tested for the measurements of patient’s heart activity and

respiration.

Figure 3.5: Simplified block scheme of Immoreev UWB radar.

Results of the developed radar confirmed the ability of the UWB tech-

nique to detect moving targets not only in medical analysis, but also for

other applications. The same authors listed the fields of application for UWB

radars in [65, 14]. In these papers, applications of UWB radar for cardio-

respiratory monitoring, for detection of live people behind barriers and for

the monitoring of guarded perimeter line are experienced by using UWB

radar prototypes, demonstrating that UWB radars can be successfully ap-

plied in all cases when a high accuracy remote monitoring of moving objects

at short distances is needed.

A technique for evaluating shape and position of a UWB pulse in noisy

data [66] has been presented by Pourvoyeur et al. in 2002. This technique

42

is based on the Continuous Wavelet Transform (CWT) through which the

received impulse can be completely characterized by four parameters, by

using a complex extension of the signal and the mother wavelet and with

the knowledge of only the approximate pulse shape. A test radar was built

to have a real radar reflection data (Fig. 3.6). The used pulse generator

was from the Picosecond Pulse Labs, the transmitting and the receiving

antenna were similar UWB antenna, the receiver was the Tektronix 11801C

sampling oscilloscope and the target was a metallic plate. Wavelet-based

impulse reconstruction was used to evaluate the exact position of the plate

with very good results.

Figure 3.6: Pourvoyeur UWB radar test set up.

A UWB radar for non invasive respiratory movement monitoring of hu-

mans behind walls (Fig. 3.7) was analysed by Ossberger [13] in 2004. Two

different types of UWB sources was used in that work: the first one from

Picosecond Pulse Labs, while the second one was developed by the authors

using step recovery diodes (SRDs). The transmitting and receiving antennas

were horn antennas. The sampling of the received signal was performed by a

sampling oscilloscope, triggered by the pulse generator. The signal processing

was carried out with a Continuous Wavelet Transform (CWT) algorithm that

allowed for the determination of the respiratory frequency and the breathing

activities up to a distance of 5 meters, also taking into account the presence

of walls.

43

Figure 3.7: Breath activity monitoring measurement set up.

UWB measurements in indoor environment using a simple UWB trans-

mitter and receiver [67] was presented by Yeap et al. in 2004 (Fig. 3.8).

The UWB source was generated using a low cost sub-nanosecond impulse

generator triggered by a rectangular pulse and transmitted with a Skycross’s

UWB antenna. The UWB signal received by the antenna was amplified by

an UWB low noise amplifier. Results of the frequency spectrum and time

domain waveform of UWB signal transmitted and received over distances in

the range of 0.3 m to 2.0 m between the UWB transmitter and receiver were

shown.

Figure 3.8: Yeap test set up.

UWB radar measurement techniques and results for medical imaging us-

ing a human phantom as well as the realistic human body were presented in

[68]. Fig. 3.9 shows the transceiver block diagram. The transmitter consists

of a pulse source connected to a TEM horn antenna. The pulser generates

44

a uniform sequence of 100 ps at 1 MHz RR. The TEM horn differentiates

the pulse to produce a radiated l80 ps (10% Vpp) monocycles. The receiver

consists of an identical TEM horn connected to an LNA, which is connected

to a digital sampling oscilloscope.

Figure 3.9: Block diagram of the transceiver.

A further feasibility study of a monostatic radar based on a commercial

UWB communications transceiver by Motorola’s Freescale Semiconductor

has been conducted by Bilich in 2006 [11]. In that work, the author checks

if the same commercial transceiver could be used both as radar for remote

sensing and for communications. Several physiological signals could be mea-

sured, but the heart rate (HR) variability was chosen by the author due to its

importance. For the sake of simplicity, the heart was considered as a spher-

ical isotropic scatterer in the far field. The maximum range, for the heart

was about 20 cm. However, it could be increased it about 1 m to provide

more flexibility and adaptability to the application, for example acting on

the system parameters. Furthermore a lot of points have to be better in-

vestigated, such as the determination of the radar cross section of the heart,

the variation of the antenna performances when placed at the interface with

tissues, and so on.

In 2007, a feasibility study of a novel fully integrated 3.1 - 10.6 GHz UWB

pulse radar on silicon for the heart monitoring was published by Zito et al.

45

Figure 3.10: Block diagram of the fully integrated UWB radar for the detec-tion of heart and breath rates proposed by Zito et al.

[16]. In that work, the principles of operation of a UWB radar for the de-

tection of the heart beat and breath frequencies are presented. A theoretical

model of the channel in which the pulse propagates are developed and system

simulations, by Ptolemy simulator within the CAD tool ADS2005ATM by

Agilent Technologies, are performed in order to prove the feasibility of such

fully integrated UWB radar. The overall system (Fig. 3.10) was shown in a

previous work [69]. It consists of a fully integrated UWB radar sensor and

a low-power IEEE 802.15.4 ZigBee radio interface, which collects the data

provided by the sensor and sends them to an acquisition unit or even on the

internet by means of a personal server. The authors claim that the radar

system and interface can be realized by means of a standard CMOS 90 nm

by STMicroelectronics (STM).

A UWB pulse radar system using correlation detection [70] has been

presented by Dederer et al. in 2007. A block diagram of the radar system

is shown in Fig. 3.11. The system comprises two monopole antennas, two

pulse generators, an LNA, two single-ended to differential converters, a four-

quadrant Gilbert cell multiplier and an additional buffer amplifier to drive

the 50 Ω measurement environment. It was designed and fabricated using

the commercially available 0.8 µm ATMEL SiGe2 HBT technology system.

Results show a resolution capability of the system in the millimeter range.

46

Figure 3.11: Dederer et al. block diagram system.

Figure 3.12: Block diagram of Leib et al. UWB radar system.

An impulse based radar system operating in the UWB frequency range

for medical applications [71] has been presented by Leib et al. in 2009. In

Fig. 3.12 the detailed block diagram of the realized bistatic UWB radar is

depicted. The transmitter consists only of a pulse generator and an antenna,

while a correlation principle is applied for the receiver. Successful measure-

ment results of vital signals and the thorax excursion of a human being in a

laboratory environment were shown. Furthermore, Leib et al. in 2010 showed

advanced signal post-processing by deconvolution with a Wiener filter that

47

led to an improved resolution performance for the realized UWB radar sys-

tem [72]. Promising results showed that small targets can be identified in

a multi-target scenario, thus the movement of small targets, i.e. the heart

muscle within the human body, could be detected directly.

3.3 Discussion

The above mentioned papers are classified in this Section with the year of

publication, a short description of the main features, and results. This clas-

sification is also based on the receiving techniques.

In the range gating technique (Table 3.1), the output of the receiver is

directly the time behavior of the breath activity [12, 5, 64, 65, 14].

Correlation techniques [70, 71, 72] allows to extract the target position

from the delay between the incoming pulse and a reference signal.

Finally, sampling oscilloscopes based on equivalent time sampling can be

used to reconstruct the time behaviour of the incoming signal [66, 13, 67]

from which the time behaviour of the breathing activity can be obtained by

using cross correlation or wavelet techniques [66, 13].

48

Author Year Main Features Results

McEwan [12] 1994 noise generator, RCderivator, wire dipoles,and bow-tie antenna

detection of heart beatsand arterial pulses (sur-face contact)

Azevedo [5] 1996 same of [12] signal correlated tobreath and cardiacactivity

Staderini [2] 2002 similar to [12, 5] predicted attenuationof pulse-echo intensitytraveling from the TXto the RX antenna

Immoreev [64] 2002 oscillator and shaper,dipole antenna

oscillograms and spec-trograms enable to per-form monitoring of peo-ple vital activity

Zito [16] 2007 CMOS technology theoretical channelmodel system analysisby CAD simulations

Table 3.1: UWB radar systems using range gating receiver.


Dederer [70] 2007 5th derivative Gaus-sian pulse, differentialmixer, 0.8 µm SiGeHBT technology

range resolution in themm range

Leib et al. [71] 2009 time delay adjustmentusing a variable phasesetting for the triggersignals

measurements of hu-man vital signs achie-ved with success

Leib et al. [72] 2010 signal post-processingwith a Wiener filter

improved resolutionperformance for therealized UWB radarsystem

Table 3.2: UWB radar systems using correlation detection.

49


Pourvoyeur [66] 2003 pulse generator andpulse forming networkCWT technique, Tek-tronix 11801C sam-pling oscilloscopes

received impulse re-construction by 4 pa-rameters without pulseshape knowledge

Ossberger [13] 2004 CWT method PPLpulser and also SRDshaper, Tektronix11801C samplingoscilloscope

detection of respira-tion with backgroundsubtraction method 5m range and 0.85 mbehind walls

Yeap [67] 2004 SRD pulse generatorSkycross’s AntennaAgilent lnfiniiumwideband oscilloscope

preliminary study andinvestigations of UWBsignal TX propagationand RX

Tan [68] 2004 pulser 100 ps (10%max amp.) at 1 MHzRR, TEM horn an-tenna, sampling oscil-loscope

multiple reflection de-tection from planar ob-ject and from scatteredsignal of the heart andstomach cross sections

Table 3.3: Assembled UWB radar systems.

50

Part II

Circuit Model for the Design of

a UWB Radar System

51

Chapter 4

UWB Radar Model

In this Chapter a circuit model for the design of a UWB radar is presented.

The model includes the signal source, the transmitting and receiving antenna,

and the presence of the human thorax.

4.1 Circuit Model

The proposed model takes into account the UWB source with its internal

impedance, the antenna characterized by its radiation impedance and effec-

tive length, the medium in which the electromagnetic field propagates, and

the scattering body.

In Fig. 4.1 the several elements composing the model can be seen, while

Fig. 4.2 shows the Microwave Office (MWO) implementation of the model.

The UWB source has been simulated inside the commercial CAD MWO

by using a piecewise voltage source. The time behaviour of the source’s

signals are Gaussian pulses, monocycle pulses, and impulse gated sinusoids

(IGSs) with a given repetition rate (RR).

The time behavior of the Gaussian pulse is given by:

Vs(t) = V e−12( t−t0σ )

2

(4.1)

where t0 is the time at which the impulse reaches its maximum value (V ).

According to Eq. 4.1, when t − t0 = σ, then Vs(t) ∼= 0.6 V . Moreover, the

53

Figure 4.1: Scheme of the UWB radar system model.

54

Figure 4.2: Circuit model of the UWB radar system as implemented withinMWO.

55

power density frequency spectrum is reduced of 20 dB at f = 1/(3σ).

A monocycle is the derivative of the Gaussian pulse and is expressed by:

Vs(t) = V√e

(t0 − t)σ

e−12( t−t0σ )

2

(4.2)

The monocycle reaches its maximum value V when t− t0 = σ.

Finally, the impulse gated sinusoid with a frequency spectrum centered

at fc is given by:

Vs(t) = V sin [2πfc (t− t0)] e−12( t−t0σ )

2

(4.3)

The internal impedance of the source (RS) has been assumed equal to 50 Ω.

The antenna radiation impedance has been modelled through an impedance

whose complex value, as a function of the frequency, is assigned in the form

of a table. This allows to study antennas whose radiation impedance is

evaluated either with electromagnetic CAD simulations or by means of mea-

surements.

For taking into account the transmitting properties of the antenna, the

following far field formula has been used [73]:

E (r, ϑ, ϕ) = jωµ0N(ϑ, ϕ)e−jβr

4πr(4.4)

where the magnitude of N(ϑ, ϕ) represents the antenna radiation pattern,

which depends on the current density distribution along the antenna.

In the direction of maximum radiation, Eq. 4.4 can be simplified as [73]:

E (r) = jωµ0lEIAe−jβr

4πr= EA

e−jβr

4πr(4.5)

where IA is the current flowing in the radiation impedance, and lE is the

antenna effective length considered as a complex quantity.

With reference to the receiving properties of the antenna, the open-circuit

received voltage in the presence of an incident field (ES) is given by:

VIN = lEES (4.6)

56

In order to implement Eq. 4.5 inside the model, a circuit block has been

introduced (see lE in Fig. 4.1 and 4.2). In particular, the complex lE value,

evaluated with electromagnetic simulations or by means of measurements, is

inserted as a function of the frequency by a user supplied table (see Fig. 4.2).

For the computation of the transmitted electric field in Eq. 4.5, a current

proportional to IA is sent through the impedance by means of a current-

controlled current source (CCCS in Fig. 4.2), with a gain equal to ωµ0 and a

90° phase shift with respect to the input current. In this way, a voltage equal

to jωµ0lE IA is obtained at the voltage-controlled voltage source (VCVS in

Fig. 4.2) output. A similar circuit block is adopted for implementing Eq.

4.6. In this case, a voltage-controlled current source (VCCS in Fig. 4.2) is

used with unitary gain.

The remaining part of Eq. 4.5, that models the air propagation, is im-

plemented by means of a lossy transmission line, with the air characteristic

impedance (Z0 = 377 Ω). The line accounts for the field phase shift and

spherical attenuation with the distance. Since the transmission line model

(TLINP) in MWO requires the attenuation per unit length (A) in dB/m, its

value is computed as:

A =1

r[20log10(4π) + 20log10(r)] (4.7)

The propagation model allows to include the presence of a transversally

indefinite wall located between the antenna and the target. The wall can be

included by splitting the line, that models the air propagation, in two parts

of length r1 and r2 and inserting between them a further line of length w (see

insert in Fig. 4.2). The characteristic impedance of this last line is related

to the wall electrical properties and its attenuation is given by Eq. 4.7 with

the addition of a term equal to 8.686αw, where α (m−1) is the attenuation

constant depending on the conductivity and permittivity of the wall.

Finally, the back-scattered field (ES) at a distance “r” from the target,

which is used in Eq. 4.6, can be evaluated by means of the equation:

ES = EISRRCS√

4πe−jβr

4πr= ESC

e−jβr

4πr(4.8)

57

where EI is the field impinging on the target and the SRRCS absolute value

represents the square root of the target radar cross section. To implement

Eq. 4.8, a circuit block similar to those used for implementing Eq. 4.5

and 4.6, allowing to insert the values of the SRRCS real and imaginary

parts at various frequencies, has been adopted. It is worth noting that in

previous papers [2, 74], only simplified indefinite planar models of the target

were considered, providing a rather coarse approximation of the thorax back

scattering.

In conclusion, the model is completely determined when the radiation

impedance, the effective length, and the SRRCS are assigned as a function

of the frequency, together with the source characteristics (time shape, am-

plitude, repetition rate), the propagation medium, and the antenna-target

distance.

4.2 Numerical Validation

For a numerical validation of the proposed model two simple scenarios have

been considered (Fig. 4.3). The first scenario consists of a metallic panel

exposed to a dipole antenna, while the second one is similar to the first

one, but takes into account the presence of a wall (dashed lines in Fig. 4.3)

between the antenna and the target.

In both scenarios, the dipole has a length of 3 cm, 1 mm diameter, and

is placed at a distance of 1 m from a metallic panel 30 cm wide and 45 cm

high.

The validation is performed by comparing the circuit model responses

with those obtained by using the electromagnetic CAD Microwave Studio

(MWS). To this end, the model parameters are preliminarily extracted, then

the model time responses are computed and compared with those achieved

with MWS.

58

Figure 4.3: Scheme of the considered simplified scenario.

4.2.1 Model Parameter Extraction

Fig. 4.4(a) shows the radiation impedance of the dipole in the 0 - 10 GHz

band computed by means of electromagnetic simulations performed by using

MWS. From the figure, a resonance frequency at about 4 GHz is evident, in

agreement with the theory of thick dipoles.

The effective length (lE) of the dipole has been obtained exposing the

antenna to a plane wave, with an electric field ES having intensity and phase

of 1 V/m and 0°, respectively, and evaluating the absolute value and phase

of the voltage at the antenna feed point. The real and the imaginary parts of

the lE to be inserted in the model can be easily computed from the obtained

results (Eq. 4.6). The frequency behavior of lE is shown in Fig. 4.4(b)

and evidences, for the absolute value, a low frequency value of about 1.5 cm,

corresponding to half of the dipole length, in agreement with the short dipole

theory [73].

The panel SRRCS has been obtained both from analytical expressions and

59

Figure 4.4: Radiation impedance (a) and effective length (b) of the dipoleobtained by means of numerical simulations with MWS as a function of thefrequency.

by means of electromagnetic simulations. To compute the SRRCS, the panel

is exposed to a plane wave with an assigned electric field EI and the scattered

field ESC is computed at a distance “r” in the far field of the scatterer along

the incidence direction. In this way, the SRRCS can be computed through

the equation:

SRRCS = SRRCSejϕSRRCS =ES

EI

r√

4πejβr (4.9)

The obtained SRRCS magnitude and phase values are shown in Fig.

4.5(a) and (b), respectively. Fig. 4.5(a) also shows the SRRCS absolute

value obtained from the analytical expression [75]:

|SRRCS| =√

4π

(w h

λ

)(4.10)

The figure highlights a very good agreement between values computed by

Eq. 4.10 and MWS simulations. For the considered rectangular PEC, the

phase angle of the SRRCS, computed with MWS and reported in Fig. 4.5(b),

60

can be expressed as: ϑSRRCS(f) = −π/2 − ϑϕi(f) where π/2 is the physic

optics result [75] and ϑϕi(f) is an additional phase angle that depends on the

scatterer geometry and frequency.

It is interesting to note that, although at the highest considered frequency

(i.e., 10 GHz ) the far field starts at a distance of about 16 m from the metallic

panel, results very similar to those reported in Fig. 4.5 have been obtained

by computing the SRRCS at distances shorter than one meter. This can be

explained taking into account that, in the considered exposure conditions,

the SRRCS is mainly influenced by the field reflected by the target, while

diffraction effects play a minor role.

4.2.2 Validation Results

Time behaviors of electric fields and voltages at various points of the con-

sidered scenario have been computed both with the proposed model and by

using electromagnetic simulations with MWS.

First of all, the free-space electric field produced by the dipole, excited

Figure 4.5: Comparison between the MWS simulated and the analytical Eq.4.9 absolute values of SRRCS of the considered PEC panel (a); simulatedphase of the panel SRRCS as a function of the frequency (b).

61

by two different Gaussian pulses and by an impulse gated sinusoid, has been

considered. Fig. 4.6(a) shows the comparison of the time behavior of the

electric field at a distance of 80 cm from the dipole, evaluated by MWS

and by the proposed circuit model, , for a Gaussian pulse with V = 1 V,

t0 = 4 ns, σ = 250 ps, resulting in a 20 dB bandwidth B of about 1.35 GHz.

Figure 4.6: Comparison between the electric field 80 cm away from the dipoleachieved with the model and by means of simulations with an exciting Gaus-sian pulse (a) σ = 250 ps, (b) σ = 125 ps, and (c) IGS with σ = 300 ps.

Fig. 4.6(b) and (c) show the same comparison for an impulse with σ =

125 ps and B ∼= 2.70 GHz, and for an IGS with V = 1 V, fc = 1.6 GHz,

σ = 300 ps, and a bandwidth B = 2.20 GHz, respectively. All the figures

show an excellent agreement between the electromagnetic simulations and

the model results with signal time behaviors following approximately the

second derivative of the source signal.

Fig. 4.6(b) also highlights in the signal tail the ringing effect due to the

field reflections at the antenna open ends not present in the signal of Fig.

4.6(a). This is due to the fact that the σ = 125 ps Gaussian pulse has a wider

frequency bandwidth with respect to the σ = 250 ps impulse, and hence a

wider portion of the signal spectrum is located in the resonance region of the

antenna.

Moreover, Fig. 4.6(b) evidences, a five time increase in the field peak

level of the σ = 125 ps with respect to the σ = 250 ps impulse. This is

62

due to the fact that the shorter impulse has a wider frequency bandwidth

interesting regions in which the antenna is a better radiator.

A further increase in the peak levels is obtained by using the IGS whose

power spectrum has the same cut-off frequency of the σ = 125 ps impulse but

has negligible values at low frequencies where the antenna loses efficiency.

Fig. 4.7 shows the signal received at the dipole feed after the reflection

from the PEC panel (see Fig. 4.3), when a Gaussian pulse with σ = 250

ps is used as excitation signal. The received voltage time behavior reported

in Fig. 4.7 follows the fourth derivative of the source signal. This is due to

the frequency behavior (∝ jω) of the radiation impedance (Fig. 4.4(a)), the

target SRRCS (Fig. 4.5(b)) and the radiated electric field (Eq. 4.4).

The frequency spectrum reported in Fig. 4.7(b) outlines the high-pass

behavior of the antenna. Both figures show a good agreement between MWS

simulations and model results. The low levels obtained are due to the low

antenna gain and the source-antenna mismatch.

Figure 4.7: Time (a) and frequency (b) behaviors of the received voltage atthe dipole feed, achieved with the model and by means of electromagneticsimulations, after the reflection from the PEC panel 1 m away from theantenna. Exciting Gaussian pulse with σ = 250 ps.

63

It is interesting to note that the σ = 250 ps impulse takes 6.742 ns to

cover the antenna-panel roundtrip with a temporal delay of about 76 ps

with respect to a signal travelling at the speed of light. This delay is due to

the frequency dependence of the antenna radiation impedance and effective

length, and the target SRRCS. This result shows that the considered model

is able to evaluate the roundtrip delay with a higher accuracy with respect

to simplified models considering the signal travelling at the speed of light.

The above reported study has been repeated by using as source a Gaussian

pulse with σ = 125 ps and an IGS with σ = 300 ps. Fig. 4.8 shows a

comparison between the received signal computed by the model and by means

of electromagnetic simulations (MWS). Also in these cases a good agreement

can be observed between the two approaches.

Finally, a further study has been performed considering the scenario re-

ported in Fig. 4.3 and inserting a transversally indefinite wall (dashed lines)

between the antenna and the panel. The wall, with permittivity εr = 2.3

Figure 4.8: Comparison between the received signal at the dipole feed,achieved with the model and by means of simulations, after the reflectionfrom the PEC panel 1 m away from the antenna. Exciting Gaussian pulsewith σ = 125 ps (a); IGS with σ = 300 ps (b).

64

and conductivity σ = 0.4 S/m [76], has a 10 cm thickness and is placed 50

cm far from the dipole. Fig. 4.9 shows the time behavior (a) and spectrum

(b) of the received voltages computed by using both the proposed model and

MWS. Fig. 4.9(a) shows at early times the presence of a strong reflection

due to the wall, followed by the reflection due to the target. The presence

of the wall halved the target signal amplitude with respect to the free space

case (see Fig. 4.7(a)). Finally, it is interesting to note that the presence of

the wall produces multiple resonances in the received signal spectrum that

are well reproduced by the model (see Fig. 4.7(b)).

4.3 Experimental Validation

In order to further validate the proposed circuit model, an experimental set-

up has been used. A similar scenario as the one depicted in Fig. 4.3 is

considered.

Figure 4.9: Time (a) and frequency (b) behaviors of the received voltage atthe dipole feed, achieved with the model and by means of simulations, whena transversally indefinite wall is present between the antenna and the target.Exciting Gaussian pulse with σ = 250 ps.

65

4.3.1 Experimental Set-Up

An experimental set-up to perform UWB radar measurements has been re-

alized, as shown in Fig. 4.10. Such system implements an indirect time

domain reflectometry (TDR) technique by way of a vector network analyzer

controlled, through an IEEE 488 interface, by a LabVIEW virtual instrument

running on a laptop. Arbitrary shaped signals can be generated, and the tar-

get reflections visualized. Moreover, the set-up allows the use of various kinds

of UWB antennas.

Fig. 4.11 shows the scheme of the implemented technique. The network

analyzer measures the complex reflection coefficient S11(f) at the input of

the antenna due to the presence of a scattering body at a given distance.

The S11(f) is acquired in a given number (NC) of frequency points with

an assigned frequency resolution FS (e.g. NC = 300, FS = 10 MHz ). At

the same time the software generates one of the possible input signals VS(t)

as in Eq. 4.1 and 4.3 with a fixed temporal resolution (tS) and a sample

number NS so that tS × NS = 1/FS = TS (e.g. ts = 10 ps, NS = 10000,

TS = 100 ns). Then, the source signal is Fourier transformed generating

the bilateral spectrum VS(f) allocated between ±NS/2TS with a frequency

resolution equal to FS.

After generating the negative portion of the reflection coefficient spec-

Figure 4.10: Scheme of an indirect UWB system.

66

Figure 4.11: Flow chart of the operation performed by the indirect TDRsystem operating as UWB radar.

67

trum, exploiting the relation S11(f)=S∗11(f), a zero padding is performed on

the reflection coefficient S11(f) obtaining the S′11(f) spectrum with the same

NS samples of VS(f). The response VR(f)=S′11(f)× VS(f) is computed and

inverse Fourier transformed, thus obtaining the time behavior of the reflected

signal VR(t).

In realistic operating conditions, the VR(t) signal is strongly influenced

by early-time reflections due to the impedance mismatch between the source

and the antenna. To remove these reflections, the proposed TDR technique

acquires preliminarily the reflection coefficient of the antenna radiating in

free space SFS11 (f), and subtracts the calibration signal VFS(t), obtained by

anti-transforming the V FSR (f)=SFS

′11 (f)×VS(f), to the reflected signal VR(t).

In this way, the calibrated signal VCR(t) is due only to the target reflection,

from which the target movements can be extracted.

4.3.2 Model Parameter Extraction

The experimental set-up described in Section 4.3.1 has been used to further

validate the proposed circuit model. The considered radiating structure is

a Seibersdorf PCD 8250 biconical antenna, matched in the 80 - 2500 MHz

band. The scattering target is a rectangular copper panel (45 × 30 cm),

similar to that used in the numerical validation of the model, placed 50 cm

away from the antenna.

In the following, the procedure used to extract the model parameters will

be described and the time behaviors of the voltage received by using various

source signals will be presented.

The Seibersdorf PCD 8250 datasheet reports the absolute value of the an-

tenna reflection coefficient and of the antenna factor (AF) as a function of the

frequency between 80 and 2500 MHz. Since the proposed circuit model needs

the complex radiation impedance, this has been obtained through measure-

ments of the antenna reflection coefficient by using the Agilent PNA E8363B

vector analyzer. Fig. 4.12(a) shows the real (RR) and imaginary (XR) parts

of the biconical dipole radiation impedance thus obtained.

With reference to the antenna effective length, to be used in the circuit

68

model, starting from the antenna factor values, reported on the PCD 8250

datasheet, the absolute value of the antenna effective length has been evalu-

ated by using the equation [77]:

Figure 4.12: Conical dipole radiation impedance (a) and effective length (b).

|lE| = 2

√RR

R0

10−AF20 (4.11)

where R0 = 50 Ω.

The obtained lE absolute values have been interpolated through a 9th-

order polynomial and are reported in Fig. 4.12(b). The low frequency values

of |lE| are lower than half of the antenna length that is about 15 cm. This

should depend on the presence of a resistive matching at the antenna input

used to enlarge its bandwidth. The presence of this resistance is also visible

in the low frequency behavior of the real part of the radiation impedance

(Fig. 4.12(a)) that considerably differs from the usual behavior, growing

with the frequency.

The lE phase was not available in the datasheet and a linearly decreas-

ing frequency behavior has been chosen so as to reproduce the signal delay

observed in the experimental measurements. Finally, since the target is the

69

same used in the numerical validation, its SRRCS has been considered equal

to that reported in Fig. 4.5.

4.3.3 Experimental Results

Experimental results have been obtained using as excitation signal a Gaussian

pulse with V = 1 V V, t0 = 10 ns, and σ = 500 ps, and a monocycle pulse

with V = 1 V V, t0 = 10 ns, and σ = 500 ps.

Fig. 4.13(a) shows the comparison between the time behaviors of the

measured signals and those achieved with the proposed circuit model using

as excitation the Gaussian pulse. The figure shows a very good agreement be-

tween measurements and simulations in the early time contents, while some

discrepancies are visible in the late times due to the simplified linear fre-

quency behavior of the antenna effective length phase. A good agreement

between measured and simulated voltages is also observed in the signal fre-

quency spectra (see Fig. 4.13(b)).

Similarly, Fig. 4.14 shows the comparison between the time behaviors of

the measured signals and those achieved with the proposed circuit model,

using as excitation the monocycle pulse. From this figure, the same consid-

erations of the previous described results can be deducted.

A further experiment has been performed by using the TDR option avail-

able in the PNA. This option allows to excite the antenna with impulses

with a given bandwidth and to visualize both the frequency and the time re-

sponses. In this experiment, the measured signals evidenced that the target

reflections were completely covered by the antenna reflections. This problem

is overcome in the proposed LabVIEW controlled experimental system, as

just shown, removing antenna reflections at each acquisition (see Fig. 4.11).

70

Figure 4.13: Time (a) and frequency (b) behaviors of the received voltage atthe conical dipole feed, achieved with the model and by measurements, afterthe reflection from the PEC panel 50 cm away from the antenna. ExcitingGaussian pulse with σ = 250 ps.

Figure 4.14: Received signal from the copper panel 50 cm far away from theantenna, using as excitation signal a monocycle pulse.

71

Chapter 5

Feasibility Study

In this Chapter, the circuit model validated in Chapter 4, is used to perform a

feasibility study of a UWB radar system for breath activity monitoring. The

model parameters are the source amplitude (Vi), the repetition rate (RR)

and time length (σ) of the impulses, the antenna return loss (S11) and gain

(G), the antenna-body distance (d), and the square root of the radar cross

section (SRRCS) of the human body.

5.1 Meeting the FCC mask

In order to meet the FCC mask [18], the source (amplitude, bandwidth, and

repetition rate) and the antenna return loss and gain must be conveniently

chosen, since in the 3.1-10.6 GHz, the EIRP has to satisfy:

EIRP = PIN G ≤ −41.3 dBm/MHz (5.1)

Furthermore, the signal to noise ratio (SNR) at the output of the receiver

must comply with:

SNRoutdB = Si − kTB −NF > 10 dB (5.2)

where k is the Boltzmann constant (1.38 × 10−23 JK−1), T is the equiv-

alent temperature of the antenna, NF is the receiver noise figure, B the

73

bandwidth of the receiver, and SNRoutdB is the signal to noise ratio at the

output of the receiver.

5.1.1 Antenna Parameter Extraction

To achieve reduced dimensions of the device and to use a low cost technology

UWB printed antennas have been used. Therefore, the return loss and the

gain of typical UWB antennas have been considered.

Gain values for these antennas are between 2 and 8 dB [78, 79, 80, 81, 82]

in the whole UWB frequency band. For this reason, in the following study,

the value of the gain has been chosen constant and equal to 7 dB.

The radiation impedance (ZRAD) of the antenna has been modeled, in

the 3.1 - 10.6 GHz band, with a 50 Ω resistor (R). This is a reasonable

assumption due to the fact that the antenna has to be well matched in its

operating band. Moreover, the absolute value of the effective length has been

computed by using the equation [73]:

|lE|2 =λ2

π

G(f)R

ζ0(5.3)

where G(f) is the gain as a function of the frequency. The lE phase has been

assumed equal to zero.

5.1.2 Source Parameter Extraction

Taking into account the model parameters of the UWB antenna described

in the previous Section 5.1.1, a study to compute the radiated EIRP has

been conducted, in function of the source applied to the UWB antenna. In

particular, the source has been simulated inside the commercial CAD MWO

by using a piecewise voltage source.

The considered UWB source signals are Gaussian pulses and its deriva-

tives. The time behavior of the Gaussian pulse is given by:

Vs(t) = V0e− 1

2( t−t0σ )2

(5.4)

74

where V0 is equal to 1 V and σ has been chosen equal to 51 ps. The source

repetition rate (RR) has been initially set equal to 10 MHz.

The first derivative of the Gaussian pulse, i.e. the monocycle pulse, is

expressed by:

Vs(t) = V0

√e

(t0 − t)σ

e−12( t−t0σ )

2

(5.5)

By deriving subsequently the previous expression, the higher order deriva-

tives can be obtained.

The radiated EIRP has been computed by using the Gaussian pulse and

its higher order derivatives.

Fig. 5.1 shows that by increasing the order of derivation, the correspond-

ing spectrum move towards higher frequencies. In particular the FCC mask

limit, in this case, is fulfilled when the third, fourth or fifth derivative of the

Gaussian pulse are used.

Figure 5.1: Computed EIRP in function of the various input signals.

By choosing the fourth derivative of the Gaussian pulse, given by:

Vs(t) = V0

[(t− t0)4

σ8− 6(t− t0)2

σ6+

3

σ4

]e−

12( t−t0σ )

2

(5.6)

a further study varying V0 and RR has been conducted to investigate how

75

these parameters affect the shape of the radiated EIRP. Obtained results are

shown in Fig. 5.2.

Figure 5.2: Computed EIRP in function of V0 and RR.

The figure shows that, by increasing the repetition rate RR, keeping V0

constant, the radiated EIRP assumes higher values; the same way, by increas-

ing V0, keeping the repetition rate RR constant, the EIRP tends to higher

values.

5.2 Human Body Radar Cross Section

The numerical procedure presented in Section 4.2.1 has been used for com-

puting the SRRCS of a realistic anatomical model based on the visible human

(VH) data set [61].

In particular, since the VH represents an overweight man with a height

of 188 cm and a weight of about 103 kg, a scaled version with a height of

188 cm and a weight of 80 kg (see Fig. 5.3) developed at the Department of

Information Engineering, Electronics and Telecommunications (DIET) has

been used [83], in order to have a model as much general as possible.

The obtained model simulates a subject in the resting state (RS) at the

end of the expiration phase with a lung volume of about 3800 cm3 (functional

76

Figure 5.3: Scaled visible human (VH) model.

residual capacity) (Fig. 5.4).

In order to verify if a UWB radar is able to detect the thorax movements

during breath activity, two new human models, simulating a normal tidal

77

Figure 5.4: Visible human lungs geometry.

breath (TB) and a deep breath (DB) have been realized.

For both models a diaphragmatic breathing has been considered. Indeed,

since the diaphragm has an involuntary movements, the model can be as in-

dependent as possible from the physical characteristic of the subject (height,

chest measurement, etc.) and from the the way of breathing. The thoracic

breathing, or chest breathing, vice versa depends on the subject will and vary

depending on the posture (standing, supine, sitting, etc.).

In the developed new models the lung geometry has been modified ac-

cording to [84], by adding a cell volume of about 500 cm3 and 860 cm3, in

order to simulate tidal and deep breathing, respectively.

In the tidal model, the lung volume increases both downwards, due to

a diaphragm displacement of about 2 cm, and frontally, due to enlargement

of the rib cage (Fig. 5.5(a)). In the deep case, the frontal displacement is

similar to the previous one, while the diaphragm goes down of further 4 cm

(Fig. 5.5(b)).

The utilized numerical dataset is made of 188 cubic sections of 1 cm side.

Fig. 5.6 shows the same section (no. 144) as anatomic axial image (a), as

numerical data set (b) and as plotted by Matlab (c).

The graphic in Fig. 5.7 shows the number of lung cells as a function of

78

Figure 5.5: Exhalation (a) and inhalation phases (b).

Figure 5.6: Anatomic axial image (a); VH numerical dataset (b); VH section144 depicted by Matlab (c).

the section, allowing an overall view of the levels where a lung expansion

occurs. From the figure it can be noted that, with respect to the resting

state, a lung expansion in the rib cage occurs until the section 11.

Sections from 11 to 15 present an equal number of lung cells for the

three cases (RS, TB, DB): in these sections the lung expansion is already at

the maximum and during a diaphragmatic breathing the lung are in contact

with the rib cage (at the sternum height). The reduction of lung cells in these

sections of the body is justified by the presence of the heart, that occupies

79

Figure 5.7: Lung cells in function of the sections.

the cavity between the two lungs.

The major increase of the lungs at the end of the inspiration phases, with

respect to the RS, occurs at the base of the lung, where the diaphragmatic

contraction takes place (2 sections for the TB and 4 sections for the DB).

The breath activity has been also modeled taking into account different

dielectric constants in the deflated case (RS) and inflated cases (TB and DB),

according to [62]. For the various tissues of the visible human the dielectric

parameters given in [85] have been considered.

The SRRCS has been computed at various frequencies up to 2.0 GHz.

This is the highest frequency at which, by using a computer with 8 GByte

RAM, the CAD MWS is able to simulate the visible human exposure ensuring

a good accuracy of simulations (i.e., cell side less than λ/10). The SRRCS

phase angles have been linearly interpolated obtaining: ϕ(f) = - 90 ° - m

fGHz, where m = 887 , 892 , 895 °/GHz for RS, TB, DB cases, respectively.

Fig. 5.8 (blue dots) shows the computed SRRCS absolute values as a

function of the frequency in the RS respiratory phase. Very similar results

are obtained with the other two considered models.

For comparison, measurements of the SRRCS, performed on a man with

a height of 183 cm and a weight of about 91 kg [86] are reported on the same

figure (empty green dots). The considered visible human model gives rise to

SRRCS values in good agreement with experimental results in the 0.5 ÷ 2

GHz range.

80

Figure 5.8: Frequency behavior of SRRCS absolute value in the RS respira-tory phase.

In order to extend the frequency range of SRRCS, results from Dogaru

et al. [76] have been considered. In particular, in [76] a scaled version of the

VH, similar to that considered in this work, has been used to compute the

RCS at frequencies between 0.5 and 6 GHz. The results in [76] have been

sampled with a 0.5 GHz spacing and the corresponding SRRCS absolute

values are reported in Fig. 5.8 (empty blue triangles). These data have been

interpolated by using a smooth approximation [87] (Fig. 5.8 dotted line).

Then, the whole set of data has been also approximated by an exponential

curve (Fig. 5.8 continuous line).

Finally, further simulations have been performed by considering the re-

duced visible human in the RS and by varying the lung permittivity and

conductivity in order to simulate the variations occurring during the breath

activity. In particular, the lung dielectric parameters have been assumed to

reduce of about 50% from the end-expiration to the end-inhalation phases

[85]. The performed simulations have evidenced no variations in the SRRCS

absolute values and a variation in the m coefficient of SRRCS phase angle of

about 0.25 °/GHz.

81

5.3 Breath Activity Responses

The response of the radar to the fourth derivative of the Gaussian pulse with

an amplitude V0 = 2 V and RR = 10 MHz, during the RS phase, has been

studied by comparing the smooth and the exponential approximation of the

SRRCS for a reasonable antenna-target distance of 2.5 m.

The obtained results, reported in Fig. 5.9, evidence a good agreement

between the received signals by using the two models of the SRRCS, in

particular in the region where the highest voltage values are present.

Then, the breath activity of the subject has been studied by consider-

ing the three human models corresponding to RS, TB, and DB respiration

phases.

The considered excitation signal is the fourth derivative of the Gaussian

pulse and the exponential approximation of the absolute value of the SRRCS

has been used.

The received signals, obtained with the proposed model, are reported

in Fig. 5.10. The figure shows a time delay of about 14 ps between the

signals corresponding to the RS and TB respiratory phases while the delay

Figure 5.9: Comparison of the received signals during the RS phase by usingthe smooth and the exponential approximation of the SRRCS.

82

Figure 5.10: Received signals by considering the three human models corre-sponding to RS, TB, and DB respiration phases

increases to 22 ps between RS and DB phases. This delay is mainly due to

the differences among RS, TB and DB in the phase slope of the SRRCS.

It is important to note that the delay in the received signals is signifi-

cant enough to allow breath activity monitoring through UWB technique,

provided the signal strength is above the sensitivity of commercial receivers.

5.4 Discussion

The proposed circuit model has been used to perform a feasibility study of

a UWB radar working in the FCC allocated band. To this end, an approx-

imation of the SRRCS extracted from various human models has been used

in the circuit model. The obtained results point out the ability of a UWB

radar to resolve human thorax movements during respiration.

83

Part III

Subsystem Design

85

Description of the UWB Radar

Scheme

Before considering the subsystems, the structure of the proposed radar will

be briefly described in the following. Fig. 5.11 shows the block scheme of

the UWB radar system.

The pulse repetition interval (PRI) generates a square wave having 10

MHz repetition rate. This pulse repetition source is also applied to a delay

line (DL). The three pulse generators (PG SRD) generate Gaussian pulses.

Two of these are used as strobe signals (VS) and one is sent to a shaper that

generates the 4th derivative of the Gaussian pulse. This last signal is applied

to the antenna and, once scattered by the target, arrives at the receiver input

(Vr).

First, the delay of the line (DL) is increased until it corresponds to the

round trip delay time. This condition is detected by the presence of a voltage

6= 0 at the receiver output.

Then, maintaining a fixed delay for the delay line, the output of the

receiver is proportional to the thorax movements, that give rise to a variable

delay of the received signal.

87

Figure 5.11: Block scheme of the UWB radar system for breath activitymonitoring.

88

Chapter 6

UWB Sources

In this Chapter, the design and realization of UWB sources are presented.

In particular, the main techniques for generating UWB impulses are briefly

discussed in Section 6.1. In Section 6.2 a qualitative and quantitative analysis

of the step recovery diode (SRD) working principles is conducted. Then, in

Section 6.3, the design of various kind of UWB sources is carried out. Finally,

the sources realization and measurement results are shown in Section 6.4.

6.1 Impulse Generation

The UWB source is usually constituted by a pulse repetition interval (PRI)

generator with a repetition rate (RR) in the range 0.1 - 10 MHz, some times

preceded by a noise source for the generation of pseudo random sequences

(see Fig. 6.1). These components is followed by a step-like (SL) generator

producing a fast rise-time edge.

Figure 6.1: Block scheme for the realization of UWB pulses.

89

For the generation of edges with rise-time greater than 500 ps switching

transistors or FETs can be used [12].

When shorter edges (50 - 500 ps) are required, step recovery diodes

(SRDs) [88, 89], or integrated circuits (ICs) developed for high speed fiber

optic applications [90] can be employed.

Finally, to generate edges shorter than 50 ps, nonlinear transmission lines

(NLTLs) can be used [91].

The usually employed waveforms in UWB radars are Gaussian pulses,

monocycles and higher order derivatives, obtained by cascading one or two

deriving circuits to the SL generator. Widely used are also Gaussian modu-

lated sinusoids (IGS) obtained by mixing a Gaussian pulse with a microwave

carrier [92].

6.1.1 Semiconductor Impulse Generator

The principal technique for generating a UWB impulse uses semiconductor

components with fast transition time, having the functionality of a switch.

Most used devices are FETs and SRDs. These components are limited by the

power that are able to supply and their speed of commutation. These quan-

tity are interrelated, indeed the power supplied decreases if the commutation

speed decreases.

A more promising technology for the generation of UWB impulses, able to

produce high power and hundreds Megahertz pulse repetition rate is based

on two devices: the drift step recovery diode (DSRD) and the drift step

recovery transistor (DSRT) [93].

The general block scheme for the realization of a pulse train is shown in

Fig. 6.2.

Figure 6.2: Block scheme for the realization of UWB pulses.

90

The store energy block provides to keep the energy coming from the

input generator for a period of time that depends by the requirements of

the output circuit. In order to minimize the reflections, it is necessary to

consider a matching for transferring the maximum power to the load . The

working principles of the SRD are widely discussed in Section 6.2.

6.1.2 Non Linear Transmission Lines

The usage of NLTLs allows to enhance the speed of the waveform rise time.

The basic idea consists in realizing a circuit where the propagation speed of

a wave in a given point of the line depends on the voltage in the line in the

same point. With reference to Fig. 6.3, if the wave speed at 10% of the

final voltage is lower than the wave speed at 90% of the final level, the effect

is a curve with a steeper slope. Since the rise time is defined as the time

difference between the 10% and 90% voltage value, it follows that the rise

time of the wave front is shorter [94].

Figure 6.3: NLTL effect on the wave front.

Such a transmission line is realizable through a cascade of a series of

inductances and shunt capacitors. The electromagnetic wave speed is given

by:

v =1√LC

(6.1)

where L and C are the inductance and the capacity per unit length, respec-

tively. The idea is to vary this velocity trough a component whose capacity

is a function of the applied voltage between the electrodes. A typical device

with such characteristics is the varactor diode.

91

6.2 Step Recovery Diodes

In this Section, the analysis of step recovery diodes (SRDs) is conducted.

This component is the key element for the UWB impulses generation and it

will be utilized for the design (Section 6.3) and realization (Section 6.4) of

the UWB sources.

6.2.1 Qualitative Analysis

The SRD is realized trough an intrinsic semiconductor interposed between

two semiconductors doped p and n. With respect to the other junction diode,

the SRD has the peculiarity of accumulating charge in forward biasing.

To better understand the accumulation within the diode, the four fun-

damental phases (storing, discharge, transition and interdiction) of the SRD

are analyzed in the following.

Storing

Fig. 6.4 shows the SRD in forward polarization. Because of the applied

voltage at the electrodes, the majority carriers (holes) of the p-type semi-

conductor, move in the intrinsic zone, while the electrons of the n-type semi-

conductor move towards the junction. When the holes and electrons meet in

the i zone, they recombine after a mean time τm, called the mean lifetime

of the minority carriers. In the SRD the carriers have a mean life as long as

possible.

From a quick analysis, it results that the total stored charge (not recom-

bined) in every moments is subjected to variation because of two contrasting

actions:

1. input of new charges due to the voltage at the electrodes that increase

the stored charges quantity that give rise to the forward anode current

IA;

2. the recombination of holes and electrons in the intrinsic zone that de-

crease the stored charge; in particular, the recombining charges are

92

as numerous as the stored charges are, and are as minor as the mean

lifetime is long.

When the two actions are balanced, i.e., the charge injected in the intrinsic

zone per time unit is equal to the recombined charges, the stored charge is

constant and equal to QMAX .

Figure 6.4: Forward biased SRD.

Discharge

Assuming that the generator, feeding the circuit containing the diode, changes

instantly its sign, forcing an inverse current IR in the diode, the accumulated

charges are pushed in the opposite direction with respect to the previously

one. The non-recombined charges are pushed towards the extremity of the

Figure 6.5: SRD discharge.

93

diode, emptying the intrinsic zone from the charge accumulated during the

forward biasing (Fig. 6.5).

This phenomenon origins the inverse current IR that crosses the diode; if

the resistance offered by the diode is negligible, the voltage at the extremity

of the diode is not subjected to variations with respect to the storing phase.

Transition and Interdiction

Once the emptying phase is ultimated, the diode goes back to the inverse

polarization, shown in Fig. 6.6, characterized by the presence of an inverse

voltage at the diode terminals equal to the voltage imposed by the circuit

for less than breakdown effect, that appears for inverse voltages typically of

the order of tens Volts.

Figure 6.6: Inverse biased SRD.

The transition from the emptying phase to the interdiction phase is char-

acterized by a fast voltage variation at the diode terminals. This particular

diode, thanks to a very high commutation speed, is able to generate a very

fast voltage front and consequently a signal with a very large frequency spec-

trum.

The transition velocity is described by the transition time (Tt) that is re-

lated to the diode circuit frequency band; supposing that all the components

are ideal, except for the diode, the response velocity limitations of the circuit

depend on the parasitic elements present in the diode (in particular, by the

junction capacity and the silicon resistance).

94

The open circuit diode (not loaded) introduces a cut-off frequency that

is of the order of 300 - 350 GHz. If the device is modeled with and ideal

diode, a shunt capacitor CP and a series resistance RS, the time constant

introduced is given by:

τD = RSCP (6.2)

the diode can be used for frequency f :

f<fD =1

2πτD=

1

2πRSCP(6.3)

so, the transition time is a second constrain for the diode utilization, because

the signal can not have a frequency content higher than the diode one. The

Eq. 6.3 gives the limits to the use of an SRD.

6.2.2 Quantitative Analysis

A realistic model of the diode is obtained accounting for recombination

through the continuity equation [88]:

dq

dt= i− q

τmc(6.4)

where τmc is the effective minority carrier lifetime and q is the stored charge.

The solution of the differential equation (6.4) is easily solved by a Laplace

transform:

I(s)

s=Q(s)

τmc+ sQ(s)−Q0 (6.5)

where the convention of using upper case letters for the s domain and lower

case ones for the time domain is used ( i.e. f(t) ←→ F(s) ), and Q0 is the

initial charge.

Q(s) =I

s(s+ 1τmc

)+

Q0

s+ 1τmc

(6.6)

If previously not stored charge (Q0 = 0) and a constant forward current IF

95

are present, then:

Q(s) =IF

s(s+ 1

τmc

) (6.7)

Taking an inverse Laplace transform of Eq. 6.7, we get a solution for the

stored charge as a function of the time:

QF = IF τmc

[1− e−

tFτmc

](6.8)

where QF is the charge stored from the forward current IF and tF is the

length of time for which the forward current IF is applied.

If a reverse current IR to withdraw the charge and switch the diode is ap-

plied, the required time is easily found from Eq. 6.5 with the initial charge Q0

not equal to zero, but some finite value due to the forward current injection.

Taking an inverse Laplace transform of Eq. 6.5 gives:

q(t) = −IRτmc[1− e−

tRτmc

]+ q0e

− tRτmc (6.9)

The negative sign in front of IR is due to the assumed positive value of the

reverse current, even though it flows in the opposite direction to the forward

current. When the reverse current has been flowed for some time tR, such

that all the charge is removed, the diode will snap. This time can easily be

found by solving the Eq. 6.9 for q(t) = 0.

tR = τmcln

[q0 + τmciRτmciR

](6.10)

Substituting for the initial charge q0 due to forward current injection:

q0 = iF τmc

[1− e−

tFτmc

](6.11)

gives:

tR = τmcln

1 +iF

[1− e−

tFτmc

]iR

(6.12)

96

This is usually called the snap time, tS.

If tF is long compared to τmc and iF iR, then:

tR = tS ∼=τmcIFIR

(6.13)

6.2.3 Microwave Office Model

For the simulations of the UWB source circuits based on SRDs designed in

this work, the computer aided design (CAD) MWO by AWR 1 has been cho-

sen. The CAD program libraries provide a SRD model that allows to insert

the data relating to a specific diode, through the “element options” window.

By this window (Fig. 6.7), the following step recovery model properties can

be appropriately modified:

reverse saturation current IS;

diode series resistance RS;

ideality factor N, presents in every generic model of the diode indicating

the doping conditions;

storage time TT, defined as the time storing, that is the the time in-

terval during which a current IF would store charge QMAX in absence

of recombination phenomena;

reverse voltage capacitance, CJ ;

breakdown voltage BV, provided by the supplier;

Furthermore, to better model the realistic behavior of the SRD, also the

package capacitance and inductance have been considered. The correspond-

ing equivalent circuit is shown in Fig. 6.8.

6.3 UWB Source Design

In the following sections, different pulse sources will be studied.

1http://web.awrcorp.com/Usa/Products/Microwave-Office/

97

Figure 6.7: SRD element options.

Figure 6.8: Realistic model of the SRD considering the package capacitanceand inductance.

6.3.1 Gaussian Pulse Source

A first circuit for the generation of UWB Gaussian pulse is shown in Fig.

6.9. This circuit, implemented on microstrip structures, includes a SRD and

a short circuited shunt stub; it is based on the well-known technique using the

delay-line principle [95]. In order to understand the functioning of the circuit,

it is possible to analyze the wave forms present in the different sections of

the circuit itself.

Let suppose the input of the circuit be an ideal square wave signal Vs(t)

with a frequency f0. During the period when the input signal coming from

98

Figure 6.9: UWB Gaussian pulse generation circuit.

the generator is positive, there is an accumulation of charge in the intrinsic

zone of the diode. When the voltage given by the source changes its sign,

the diode enters in the discharge phase of the accumulated charge; in such a

phase, the diode behaves like a constant IR generator.

Once the accumulated charge is exhausted, the fundamental transition

for the functioning of the circuit happens: the voltage at the heads of the

diode changes quickly, with a speed constrained by the temporal constant

introduced by the parasitic capacity of the diode. This quick voltage variation

produces a current wave in the parallel between the resistance and the line of

transmission. At the end of the line, the wave is reflected on the resistance

generating the desired voltage impulse [96].

Fig. 6.10 shows the circuit schematic implementation within MWO. Pre-

liminarily, the circuit has been piloted by a square wave with an amplitude

of 2 V and a rise time tR = 2 ns. The SRD considered to set the element

options within the MWO CAD is the SRD DVB-6723 or HP 5082-0885 [97],

since they present the same characteristics. The characteristic impedance of

the short circuited transmission line ZC is equal to 50 Ω.

In these conditions, as described previously, the incident wave combines

with the wave reflected by the short circuited transmission line so that the

99

Figure 6.10: UWB Gaussian pulse MWO circuit.

voltage behavior at the output of the circuit is a Gaussian like pulse.

The output voltage has been computed for various length of the trans-

mission line, showing that the Gaussian pulse amplitude and length increase

with the transmission line length (l). This can be intuitively explained from

the fact that, by increasing the transmission line length, the reflected wave

recombines with the incident wave later.

Figure 6.11: Output voltage of the circuit schematic in Fig. 6.10

100

Simulation results, for l = 10 mm, are shown in Fig. 6.11. As the figure

shows, the maximum amplitude of the pulse is V = 1.18 V and the time

length, considering the values at 60% from the maximum, is 2σ ∼= 100 ps.

Simulation results demonstrate that:

1. by increasing the line length, the time length of the impulse increases

almost linearly;

2. the impulse ripple increases with the transmission line length: indeed,

increasing the line the harmonics have to do a longer trip, and so are

subjected to a higher reciprocal phase shift. These harmonics con-

tribute to the negative voltage constituting the ripple.

Layout Implementation

The next step for the circuit study is the circuit itself implementation in

microstrip technology. The chosen substrate is the Rogers RO4003, with the

following characteristics:

permittivity, εr (@ 10 GHz ) = 3.38±0.05

substrate thickness, h 0.020” = 508 µm

copper thickness, t = 1 oz = 35 µm

copper resistivity, ρ = 0.7

loss tangent, tan δ = 0.0027

The schematic used in MWO for the layout simulation is shown in Fig.

6.12. In this schematic, the interconnection lines between the square wave

generator and the diode and also between the short circuited line and the

load are considered. The short circuit has been modeled through a via-hole.

Also the discontinuity has been considered and two emplacements for the

diode welding on the microstrip line have been taken into account.

It is worth noting that, in this simulation, the characteristic impedance of

the shorted line is set to a higher voltage. In this way, a higher peak voltage

amplitude can be obtained.

101

Figure 6.12: Layout schematic of the MWO implementation of the Gaussianpulse.

Figure 6.13: Input and output voltage of the circuit schematic in Fig. 6.12.

A package of lp = 1.15 mm and wp = 1.35 mm is considered.

The input and the respective output voltage behavior are reported in Fig.

6.13. A zoom of the output voltage achieved is also shown in Fig. 6.14.

The behavior of the signal is similar to that in Fig. 6.11, but the ampli-

tude and the time length are greater, i.e., V = 1.7 V and 2σ ∼= 150 ps. This

is due to the higher value of the characteristic impedance and to the fact that

in the layout schematic also the microstrip line connecting the input source

102

Figure 6.14: Output voltage zoom of the layout schematic in Fig. 6.12.

to the diode, and the diode to the output have been considered in order to

realize the device. Same considerations on the schematic circuit results can

be done.

Variable Delay Gaussian Sources

As it will be clearer hereinafter (see Chapter 8), it can be very useful to have

a Gaussian pulse with a variable time delay.

Such a circuit can be obtained by inserting a voltage generator with a

variable offset and a Schottky diode (Fig. 6.15); indeed, varying the offset

value the arrival time of the pulse changes. The Schottky diode provides to

have an impulse without ripple.

6.3.2 Monocycle Pulse Source

In this Section, two circuit schematics implementing monocycle pulse sources

are proposed.

103

Figure 6.15:

Monocycle pulse with a Capacitor

To generate a monocycle pulse the circuit previously described can be used,

adding a capacitor C deriving the Gaussian pulse.

Various simulations have been carried on, to value the optimized trans-

mission line length l and C. The increase the transmission line length leads

to a valuable increase of the voltage amplitude, but reduces the symmetry of

the monocycle pulse. Increasing the C value the output voltage amplitude

increases, but also the ringing raises bringing to a considerable reduction

of the percentage symmetry. The choice of the final values is the result of

some compromises, motivated by the system specifications and also by the

designer sensitivity.

Parametric simulations have been done on such a circuit, and the final

design is shown in Fig. 6.16. The final circuit parameters can be summarized

as follows:

input signal: square wave with RR = 10 MHz, amplitude V = 10 V

and tR = tF =10 ns ;

capacitor value: C = 2.7 pF ;

104

Figure 6.16: MWO circuit for the generation of a monocycle pulse.

Figure 6.17: Behavior of the output monocycle voltage.

transmission line length: l = 10 mm;

Results for the output voltage generated from this circuit are depicted

in Fig. 6.17. The figure shows that the obtained monocycle pulse so ob-

tained has a small ringing level and also a good balance between positive

and negative parts.

105


For the layout implementation of this circuit in MWO, the same consideration

of the previously described layout can be done. Fig. 6.18 shows the layout

of the circuit while in Fig. 6.19 the comparison of both circuit and layout

schematic output voltage is presented.

Figure 6.18: Layout schematic of the MWO implementation of the monocyclepulse.

Figure 6.19: Comparison between the output voltage obtained with the cir-cuit schematic and with the layout schematic.

106

Figure 6.20: Circuit for the generation of the monocycle with the short cir-cuited stub.

Monocycle Pulse with Short Circuited Stub

For the design of the monocycle generator, also the configuration that com-

prises a step recovery diode and an impulse-shaping network, converting a

Gaussian pulse in a monocycle one, have been considered. In particular, to

generate the monocycle pulse, the first derivative of the Gaussian pulse (or

the second derivative of the step) is implemented by a further short circuited

transmission line.

The circuit, simulated within the commercial CAD MWO, is shown in

Fig. 6.20.

The monocycle-pulse forming circuit is realized using the short-circuited

transmission line C and the transmission line B, used to convert an impulse

into a monocycle pulse.

The impulse from the impulse-shaping network (SRD and transmission

line A) propagates toward the short circuit and it is reflected back. Therefore

it combines with the other impulse on the transmission line B to form a

monocycle pulse at the output of the source (VOUT ).

The Schottky diode HSMS-2851 has been used to reduce the pulse ringing

thus shaping the pulse and improving the symmetry and duration. A similar

107

Figure 6.21: Time behavior of the generated monocycle pulse.

configuration has been used in [95, 98, 89].

Results of the proposed circuit are reported in Fig. 6.21; the utilized

input square wave has a rise time tR = 10 ns, fall time tF = 10 ns and

amplitude V = 10 V.


The layout of the proposed circuit is shown in Fig. 6.22, while the corre-

sponding output voltage is reported in Fig. 6.23. In addition to the layout

output signal, in the figure the time behavior of the output voltage of the

circuit schematic is also depicted. The figure shows an optimum agreement

between the two simulation results, with a monocycle time length (from the

minimum to the maximum peak) of about 280 ps and an amplitude of about

V = ± 1 V.

6.3.3 Higher Order Derivatives Source

According to Chapter 5 concerning the UWB source, the 4th or 5th order

derivative of the Gaussian pulse has to be used to comply with the FCC

emission mask.

108

Figure 6.22: Layout schematic of the MWO implementation of the monocyclepulse with two short circuited transmission lines.

Figure 6.23: Time behavior of the generated monocycle pulse.

Starting form the pulse generator described in Section 6.3.1, a shaping

network made of a 4th order band pass filter generating the 4th derivative

of the Gaussian pulse have been considered. In particular, the generated

Gaussian Pulse is further shaped by a microstrip reflection network to obtain

a higher order derivative Gaussian pulse able to comply with the spectrum

mask set by FCC.

Fig. 6.24 shows the comparison between the output voltage obtained

by the 4th order band pass filter and the analytical expression of the 4th

109

derivative of the Gaussian pulse, given by Eq. 5.6. The figure highlights a

good agreement between the two signal behaviors.

Figure 6.24: Time behaviors of the signal obtained with the designed UWBsource and with the analytical expression.

6.4 Realization and Measurement Results

Some of the circuits proposed in the previous Section have been realized by

the milling table T-Tech Quick Circuit 5000, converting MWO layout of the

circuit in “Gerber”2 file and sending this file directly to the milling table tool,

through a software interface (ISOPRO 3), allowing the physical realization

of the circuit.

As stated above, the utilized substrate is the Rogers RO4003, whose

parameters has been given in Section 6.3.1.

2A Gerber file is a file format used by printed circuit board (PCB) manufacturingmachines to lay out electrical connections such as traces, vias, and pads (the component“footprints” on the PCB). A Gerber file can also contain information for drilling andmilling the circuit board; it is generated by PCB CAD software, and are loaded into aComputer-Aided Manufacturing (CAM) system to prepare data for each step of the PCBproduction process.

3http://www.t-tech.com/products/software.asp

110

Measurements have been conducted with a sampling oscilloscope LeCroy

SDA100G Serial Data Analyzer, able to combine the high bandwidth and

accuracy of a sampling oscilloscope with the speed and flexibility of a real

time instrument. The experimental set-up is shown in Fig. 6.25

Figure 6.25: Measurements experimental set-up.

6.4.1 Gaussian Pulse Source

Fig. 6.26(a) shows the Gaussian pulse source realized device, and the cor-

responding measurement results are depicted in Fig. 6.26(b). Measurement

results and simulation results are in a very good agreement, except for the

amplitude of the pulse, that, in this case, is lower. This is due to the power

divider used in the measurement, for triggering the sampling oscilloscope

with the output of the UWB pulse generator (see Fig. 6.25).

6.4.2 Monocycle Pulse Source

The realized monocycle source, relating to the circuit with the capacitor, is

shown in Fig. 6.27(a).

The corresponding measurement results are depicted in Fig. 6.27(b).

111

Figure 6.26: Realized device for the generation of the UWB Gaussian pulse(a); measurement results (b).

Also in this case, a good behavior of the source can be observed, and similar

considerations about the amplitude of the impulse can be drawn.

Figure 6.27: Realized device for the generation of the UWB monocycle im-pulse (a); measurement results (b).

112

With reference to the circuit with two short circuited transmission lines,

the realized monocycle source is shown in Fig. 6.27(a). The figure shows

that the first transmission line has been curved, in order to make the device

more compact.

Measurement results are depicted in Fig. 6.27(b), showing a good balance

between the negative and positive peak signal, but higher ringing values can

be observed, due to the reflections of the connectors.

Figure 6.28: Realized device for the generation of the UWB monocycle im-pulse (a); measurement results (b).

113

Chapter 7

UWB Antennas

As said previously, UWB radars send very short pulses by using suitable

UWB antennas, and receive, with the same or another UWB antenna, the

echoes reflected by the target.

Several planar monopole antennas to be employed in UWB radars have

been studied, like circular, elliptical, heart-shaped [99, 81, 100, 101]; however,

all the cited radiating structures have omnidirectional properties.

In this Chapter two novel UWB printed antennas designed to be part

of a UWB radar system for cardio-respiratory activity monitoring in a non-

invasive way are presented. The two antennas have the same shape but differ

in terms of dielectric substrate and dimensions.

7.1 Antenna Design

For the UWB antenna design four main goals are required:

1. the return loss of the antenna has to be lower than -10 dB in the 3.1 -

10.6 GHz FCC band;

2. the antenna has to be portable and light;

3. the device has to be low cost;

4. the antenna has to have directive performances.

115

To fulfill these requirements printed UWB antennas can be used [99,

81, 100, 101, 102, 103, 104]. In particular, between these antennas, the

microstrip-fed monopole structure has been considered, where the radiating

element and the feeding microstrip line are realized over one of the sub-

strate faces, while on the other face, a suitable ground plane is etched. Such

structure has been chosen considering the broadband and good radiation

properties of the printed heart monopole antenna [99]. Taking into account

the directivity performance of the truncated planar configuration proposed

in [105], a half-heart shape geometry has been finally chosen. The final

half-heart shape geometry has been optimized through parametric simula-

tions and final dimensions of both the antennas for fixed and wearable UWB

systems are reported in Section 7.2 and Section 7.3 respectively.

7.2 Antenna for Fixed UWB Systems

The half−heart shape geometry has been optimized through parametric sim-

ulations using CST Microwave Studio software. The dielectric substrates

utilized in this project is the Rogers RO4003 with relative permittivity εr =

3.38, thickness h = 0.508 mm, and copper thickness t = 0.035 mm.

In Fig. 7.1 the geometry of the designed antenna is reported. The radiator

is located on the top layer of the substrate and the ground plane on the

bottom layer. The total dimensions are: l = 75.0 mm, w = 50 mm. The

shape of the half heart on the top layer is obtained trough a semicircle of

radius rc = 25 mm. The shape of the ground on the bottom layer of the

antenna is also obtained through a parametric spline. All the parameters

have been optimized to obtain the best values of the return loss to fulfill the

requirements. As we can note from the figure, the feeding microstrip line has

been curved away from the edge of the structure to ease the connection with

the coaxial feed line.

116

Figure 7.1: Geometry of the proposed antenna.

7.2.1 Antenna Performances in Free Space

Fig. 7.2 shows the return loss amplitudes as a function of the frequency for

the designed UWB antenna. The obtained results indicate that the antenna

have UWB characteristics with a return loss below -10 dB in the whole

required frequency band.

Figure 7.2: Return loss of the proposed antenna.

117

Concerning the antenna radiation pattern, Fig. 7.3 shows a polar plot at

8 GHz of the antenna to be used in the fixed system. The plot highlights

that the direction of maximum radiation is close to the x direction of Fig.

7.1 (ϑ = 90°, ϕ = 0°) with a -3 dB aperture of about 55°. Fig. 7.4 shows the

polar plot computed at 4, 6 , 8, 10 GHz.

Figure 7.3: Polar plot of the gain at 8 GHz for the fixed antenna.

Figure 7.4: Polar plot of the gain at 4, 6 , 8, 10 GHz for the fixed antenna.

118

Fig. 7.5 shows the peak gain behavior as a function of the frequency as

well as the ϕ value (θ = π/2) for which the gain achieves its maximum value.

As it can be noted from the figure, the gain values increase with the frequency.

In particular, the minimum values is 4.6 dBi while the maximum value is 9.4

dBi at 11 GHz ; these gain values are comparable with the gain values of UWB

antennas reported in literature [105]. Concerning the direction of maximum

radiation (θ = π/2), Fig. 7.5 shows that it is almost constant within ± 10°.

Figure 7.5: Peak gain behavior of the fixed system antenna and direction ofmaximum gain as a function of the frequency.

An important parameter of UWB antennas is the fidelity factor that is

determined by the peak value of the cross correlation function between the

observed pulse at a certain distance from the antenna and the excited pulse

[106, 107]:

F = maxτ

∫ +∞−∞ i1(t)s2(t+ τ)dt√∫ +∞−∞ i21dt

√∫ +∞−∞ s2

2dt(7.1)

where i1(t) is the input signal, s2(t) the ϑ component of the electric field (Eϑ)

at a certain distance from the antenna and τ is the delay to maximize F in

Eq. 7.1. Considering that, for an antenna, the response is an approximation

of the derivative of the input excitation, s1(t) = di1(t)/dt could be used in

119

Probe position Fidelity Fidelity Probe position Fidelity Fidelity(xy plane) i1(t) = s1(t) i1(t) = ds1(t)/dt (xz plane) i1(t) = s1(t) i1(t) = ds1(t)/dt

ϑ = 90° ϕ = 0° 0.947 0.983 ϕ = 0° ϑ = 0° 0.700 0.706ϑ = 90° ϕ = 30° 0.961 0.964 ϕ = 0° ϑ = 30° 0.825 0.767ϑ = 90° ϕ = 60° 0.964 0.975 ϕ = 0° ϑ = 60° 0.948 0.964ϑ = 90° ϕ = 90° 0.925 0.928 ϕ = 0° ϑ = 90° 0.947 0.983

Table 7.1: Simulated fidelity of the proposed antenna.

place of i1(t) [106]. The UWB signal used in [106, 80] is assumed to excite

the fixed antenna. This UWB signal is the 5th derivative of the Gaussian

pulse, given by:

i1(t) = C

(− t5√

(2π)σ11+

10t3√(2π)σ9

− 15t√(2π)σ7

)e−

12( t−t0σ )

2

(7.2)

where C is a constant which can be chosen to comply with the peak power

spectral density allowed by the FCC, while σ is taken equal to 51 ps to ensure

that the spectrum shape complies with the FCC spectral mask.

The fidelity factor has been calculated trough simulations at a distance

from the antenna of 100 cm and for various directions. Results concerning

the fidelity (i1(t) and its derivative) are summarized in Tab. 7.1. The values

reported in the table highlight a very high fidelity for the proposed antenna,

for all the considered directions.

Another important goal of UWB antenna design is to achieve a good

linearity dependence of the radiated field phase as a function of the frequency

in order to minimize pulse distortion and to improve the fidelity factor.

The parameter that describes the phase response of the antenna is the

group delay, defined as the negative derivative of the phase response with

respect to the frequency.

Fig. 7.6 shows the group delay values as calculated from the time-domain

response. The figure reveals that the antenna group delay is almost constant,

with less than 0.2 ns fluctuations, across the whole considered frequency

band.

120

Figure 7.6: Group delay of the proposed fixed system antenna.

7.3 Antenna for Wearable UWB Systems

The same half−heart shape geometry has been optimized through parametric

simulations using CST Microwave Studio software.

The dielectric substrates utilized is the Rogers RT6010 with relative per-

mittivity εr = 10.2, thickness h = 0.640 mm, and copper thickness t = 0.035

mm. The geometry of the designed antenna is a scaled version of the one in

Fig. 7.1 with total dimensions given by l = 48.5 mm and w = 25 mm, while

the half heart on the top layer is obtained trough a semicircle of radius rc =

12.5 mm.

7.3.1 Wearable Antenna Performances in the Presence

of a Box Model of the Thorax

In order to check the ability of the wearable antenna to monitor the heart

activity, the radiating structure has been placed in front of a box model of

the thorax. In particular, the antenna is placed at a distance of 1 cm with the

box representing the thorax, vertically aligned with it, and with the direction

of maximum radiation pointing toward the thorax (see Fig. 7.7). Inside the

121

Figure 7.7: Antenna in presence of biological tissues.

thorax, at a depth of few centimeters, a blood sphere of variable radius has

been placed to represent the presence of the heart.

For the biological tissues, the dispersive behavior based on the Cole-Cole

equation has been considered [108]: the thorax is filled with an equivalent

body tissue whose parameters have been taken from those recommended by

the IEEE SCC-34/SC-2.For the sphere representing the heart, parameters

from [62, 109] have been considered.

To simulate the heart movements, a set of simulations have been per-

formed varying the sphere radius and measuring the received voltage at the

feed point. Since the early time contents of this signal are dominated by the

antenna and skin reflection, a calibration procedure has been implemented.

The calibration signal has been calculated as an average value of all the mea-

sured voltages and has been subtracted from each received signal. In this

way the effect of the heart reflection is better evidenced in the signal time

behavior.

Fig. 7.8 shows the calibrated signals corresponding to the minimum and

maximum sphere radius, i.e. 2 cm and 2.5 cm respectively, simulating the

end-systole and the end-diastole conditions.

The figure highlights that it is possible to distinguish between the two

122

positions; in fact the corresponding signals arrive at the antenna feed point

at different time instants (about 120 ps distance between the absolute mini-

mum of the two signals) and, consequently, heart movement can be detected

through a suitable radar receiver.

7.4 Measurement Results

The two UWB antennas have been realized using a milling table and a SMA

connector has been soldered at the input of the microstrip line. The photo-

graph of the manufactured antennas including the coaxial connector is shown

in Fig. 7.9.

Return loss measurements were performed using a PNA E8363B network

analyzer and placing the antenna in an anechoic chamber.

The measured return loss for the fixed antenna printed on RO4003 is

reported in Fig. 7.10 indicating that the antenna features UWB behavior

with a bandwidth from 3.1 GHz to more than 10.6 GHz assuming a -10 dB

return loss reference.

On the same figure, simulation results carried out adding the SMA con-

nector to the antenna are also reported. A good agreement between numeri-

Figure 7.8: Received signals for two cardiac phases.

123

Figure 7.9: Realized UWB antennas

Figure 7.10: Measured and simulated return loss of the proposed antenna.

cal and experimental results is obtained. However, comparing Fig. 7.10 with

Fig. 7.2 it can be noted that the presence of the connector gets the antenna

return loss worse.

With reference to the wearable antenna, both simulations and measure-

ments have shown that the presence of the connector makes the return loss

124

worse than the one obtained without the connector model. Since the antenna

will be directly connected to a microstrip circuit, i.e. without a coaxial con-

nector, the time domain reflectometry (TDR) technique has been used to

remove the connector effect from the measured data, so as to consider only

the effect due to the antenna [110].

Figure 7.11: Measured and simulated return loss of the proposed antenna.

The obtained results are reported in Fig. 7.11, where the TDR mea-

surement results are compared with the simulation results in the absence of

the connector. The figure shows a good agreement between simulations and

measurements especially in the 3.1 - 10.6 GHz frequency band.

7.5 Discussion

Two novel UWB printed antennas have been presented. Numerical results

show a good antenna matching, an optimum fidelity factor, and an almost

constant group delay for both antennas in the whole 3.1 - 10.6 GHz frequency

band.

Furthermore, the gain values of the antenna to be used in the fixed system

has values comparable with the gain values of UWB antennas reported in

125

literature [78, 79, 80, 81, 82, 100] and used in the feasibility study (see Section

5.1.1).

Simulations are conducted considering the wearable antenna placed very

close to a box model of the thorax, with a spherical model of the heart inside.

The obtained results show that by using a UWB radar, equipped with one

of the proposed antennas, the small heart movements can be monitored.

Eventually, the two antennas have been realized and measured by a vector

network analyzer finding a good agreement between simulation and measure-

ment results.

126

Chapter 8

UWB Receivers

From the analysis of the existing literature, the reconstruction of the breath

activity time behavior, starting from the signal at the receiving antenna, can

be performed using UWB receivers based on one of the following approaches:

range gating;

correlation techniques;

sampling oscilloscope.

Each one of the above cited techniques can be used to reconstruct the

breath activity time behavior starting from the antenna received signal. How-

ever, they differ with respect to some features.

In the first case, the output of the receiver is directly the time behavior

of the breath activity [5, 20, 14].

Periodic correlation [70] allows the extraction of the target position from

the delay between the incoming pulse and a reference signal.

Finally, sampling oscilloscopes based on equivalent time sampling can be

used to reconstruct the time behavior of the incoming signal [13] from which

the time behavior of the breathing activity can be obtained by using cross

correlation or wavelet techniques [111, 13].

In this Chapter, UWB receivers based on the range gating techniques

are used, due to their simplicity and ease of implementation. Such receivers

are constituted by a diode sampling circuit driven by “strobe” signals [112].

127

In particular, the Gaussian source signal, delayed of a time equal to the

antenna-target round trip travel time, is used as strobe signal. In order to

improve the receiver signal to noise ratio (SNR), the output of the sampling

circuit is sent to an integrator with a time constant great enough to allow the

summation of many thousand samples [12, 113]. In particular, in the range

gating technique, the signal arriving from the receiving antenna is sampled

in the time instants imposed by the strobe signal. The output of the receiver

is averaged in an integrator with a time constant τ greater than the mean

pulse repetition frequency (PRF).

Typically, for a PRF of 1 µs, i.e. a repetition rate of 1 MHz, the integra-

tion interval is 10 ms, i.e., 10000 impulses have been averaged, while for a

repetition rate of 10 MHz, the integration interval is 1 ms, corresponding to

1000 impulses.

8.1 UWB Receiver Schemes

Different UWB range gating based receivers have been proposed in literature

[12, 114, 89, 2, 113]. Among them, two UWB receiver schemes have been

found to be suitable for the implementation of the specific application.

The first scheme (reported in Fig. 8.1) has been proposed by McEwan

in [12] and consists of two Schottky diodes driven in the conduction mode

by applying a short negative pulse (Vstrobe) at the cathodes. In this way, the

two capacitors (C3 and C4 in Fig. 8.1) charge with the received echoes (Vin

in Fig. 8.1).

The second scheme (reported in Fig. 8.2) has been proposed by Lee

in [113] and is made of a sampling head constituted by two identical parts

having a Schottky sampling diode, a sampling capacitor (C1 and C2), and a

resistor (R5 and R6). It samples, holds, and converts the RF signal, coming

from the receiving antenna, into a baseband signal (Vout).

The baseband circuit is composed of two resistors (R3 and R4) and a

capacitor (Cout). To amplify the baseband signal, the circuit could comprise

a baseband amplifier after the output of the receiver.

When the received pulse (Vin in Fig. 8.2) is coming from the desired tar-

128

Figure 8.1: Receiver scheme by McEwan implemented in MWO.

Figure 8.2: Receiver scheme by Lee implemented in MWO.

get, the strobe pulses put the diodes on and the capacitors are charged. Since

the sampling time is very short, the capacitors store only a little percentage

of the signal. Many pulses can be integrated to increase the voltage on the

capacitor.

Both the proposed schemes have been studied to value the best configu-

129

ration for the proposed UWB system.

8.2 Comparison

The two schemes have been compared by applying the same input voltage

and strobe signals (triangle pulses with 400 ps time length). In particular,

the amplitude of the strobe pulse is set to a peak amplitute of 1 V, while a

variable amplitude of the received RF signal is considered.

Results are presented in Table 8.1. The number of the integrated pulses

N is equal to 100 and the repetition rate RR is equal to 10 MHz.

Input ∆Vout (mV ) Vout (mV )(mV ) (McEwan) (Lee)

0 0 01 0.2 0.102110 1.3 1.634100 12.2 19.41

Table 8.1: Output voltage values obtained varying the amplitude of the inputvoltage. The strobe signal arrives in phase with the received signal.

As regards the McEwan scheme, the differential signal (Vout4 − Vout5) at

the output has to be considered.

From Table 8.1 it appears that, by increasing the input voltage, for the

Lee scheme the output voltage increases with a higher slope.

By considering an input signal of 100 mV and a variable delay between

the strobe signal and the RF impulse, the signal arriving from a target in

movement can be simulated. Table 8.2 shows that, as expected, the increase

of the time delay gives rise to a decrease of the output voltage values. In

particular, the output voltage assumes the zero value when the time delay

between the strobe signal and the received signal is exactly the total time

duration of the triangle pulse.

Furthermore, the values reported can be also amplified by the baseband

amplifier that, in general, follows the receiver output [12, 114, 89, 2, 113, 115],

and here is not considered.

130

Delay ∆Vout (mV ) Vout (mV )(ps) (McEwan) (Lee)

0 12.20 19.4150 12.00 17.94100 11.40 14.97150 9.20 11.68200 6.30 8.16250 3.80 4.46300 1.40 1.93350 0.30 0.47400 0.00 0.00

Table 8.2: Output voltage values obtained varying the time delay of the inputvoltage (N = 100).

In the presence of a delay between the strobe and the input signal, higher

output voltage are obtained by using the Lee scheme. Moreover, the Lee

scheme is more suitable for the antenna considered in our system. Indeed,

the antennas designed and realized in Chapter 7 can be easily connected to

this receiver circuit topology. Furthermore, it is not difficult to realize two

strobe signals with an opposed polarity (see Section 6.3.1). The McEwan

scheme, on the contrary, is more suitable for systems with balanced antennas

like dipoles.

The Lee scheme has been optimized for our radar system (Fig. 8.3), by

using the signal we have at the receiver input, in order to have the greater

value of the voltage amplitude when 1000 impulses are integrated. In par-

ticular, the value of the output capacity (Cout) plays a crucial role. Indeed,

changing the values Cout, the final amplitude voltage changes, but the choice

has to be made considering the number of impulses integrated.

Fig. 8.4 shows the integrated signal behavior when the strobe signal are

Gaussian pulses with a length of 200 ps and amplitude ±1 V, and the receiver

input signal is a pulse with the same duration and amplitude 10 mV. A value

of C = 10 nF gives rise to a higher value with respect to C = 100 nF and

does not present the saturation effect of the 1 nF case.

To better evidence the behavior of the range gating receiver, the output

131

Figure 8.3: Optimized receiver scheme implemented in MWO.

Figure 8.4: Integrated signal behavior for different values of the capacitor.

voltage is shown in Fig. 8.5 when N = 10 impulses are integrated. The

figure highlights the capacitor charging with each impulse. The repetition

132

rate is 10 MHz that corresponds to a pulse repetition time of 100 ns, as can

be noted in Fig. 8.5.

Figure 8.5: Integrated signal behavior with N = 10 and C = 10 nF.

8.3 Complete Model Simulations

In this Section, results obtained by inserting in the radar circuit model of

Fig. 4.1 the designed source, the antenna, and the receiver are discussed.

The model of the human body SRRCS, and the UWB antenna for the

fixed systems, able to operate in the 3.1-10.6 GHz band, proposed in Chapter

7 have been considered.

In particular, the receiver output voltage has been evaluated, by consider-

ing that the received signal is that computed with the radar model, when the

three phases of the breath activity, namely resting state (RS), tidal breath

(TB) and deep breath (DB), are considered.

Fig. 8.6 shows the receiver scheme that considers as strobe signal the

designed Gaussian source with 1 V amplitude, and as input signal that eval-

uated by using the radar model, with the 4th derivative of the Gaussian pulse,

the designed UWB antenna and the SRRCS of the VH model.

133

Figure 8.6: Scheme used for obtaining the final signal (Vout). The designedsource for the strobe signal, the antenna for the fixed systems, and the humanbody model has been taken into account.

134

∆t Vout(ps) (mV)

RS 0 17.5TB 14 15.1DB 22 3.0

Table 8.3: Simulated output voltage values obtained with the complete cir-cuit.

Figure 8.7: Lung volume in function of the time.

The antenna-body distance considered in the simulations has been as-

sumed equal to 2.5 m that is a realistic distance between the ceiling and a

patient lying in a bed in hospital confinement.

The obtained output voltage in function of the delay correspondent to

the RS, TB and DB phases is reported in Table 8.3.

Since the lung volume in function of the time is known, an estimation

of the breath activity signal can be carried out. Fig. 8.7 shows a simplified

model (sinusoid with f = 0.2 Hz [116]) of the lung volume in function of

the time. The minimum of the sinusoid corresponds to the resting state,

while the maximum to the deep breath. From Table 8.3 is possible to find an

analytic relationship between the output voltage and the lung volume (Fig.

135

Figure 8.8: Output voltage as a function of the volume (N = 100).

Figure 8.9: Signal related to the voltage signal.

8.8).

By combining the model in Fig. 8.7 with the results in Fig. 8.8, the

voltage in the function of the time can be evaluated (see Fig. 8.9).

As it is clear from the figure, the obtained voltage levels can be read with

low cost A/D converters.

136

8.4 Receiver Layout

The final optimized receiver has been implemented in microstrip technology

within the CAD MWO, choosing as substrate the Rogers RO4003. The

schematic of the receiver layout is shown in Fig. 8.10.

As it can be seen from the figure, all the interconnection lines between the

various components have been considered in the layout. The short circuit has

been modeled through a via-hole. Also the discontinuity has been considered

and the emplacements for the diode welding on the microstrip line have been

taken into account.

Fig. 8.11 shows the 3D layout schematic, with the circuit components

(Schottky diodes, capacitors, and resistors) indicated.

Figure 8.10: Receiver schematic layout.

137

Figure 8.11: Receiver 3D layout.

Results obtained with the receiver layout are in optimum agreement with

the results obtained with the circuit of Fig. 8.3, whereof in Fig. 8.4 is

depicted the behaviour for N = 10.

138

Conclusions and Future

Directions

In this PhD thesis, the study and the design of a UWB radar system for the

remote monitoring of breath activity has been conducted.

Preliminarily, a circuit model of a UWB radar system for breath activity

monitoring has been developed. The model considers the UWB source with

its internal impedance, the antenna, characterized by its complex radiation

impedance and effective length, the field propagation, and the body scat-

tering. The model has been validated by means of numerical simulations

performed using Microwave Studio. In particular, a scenario constituted by

a metallic panel exposed to a UWB impulse radiated by a dipole antenna has

been considered. The electric field in free space has been reproduced with

a good agreement between the proposed model and the EM CAD. Compar-

isons between time and frequency behaviors of the received signals at the

dipole feed, achieved with the model and by means of simulations, have been

conducted, both in the air and in presence of a transversally indefinite wall

with a good agreement between the model and simulation results.

A further validation of the model has been performed by comparing its re-

sults with those achieved by using an experimental set-up, based on a network

analyzer that implements an indirect time domain reflectometer controlled

by LabVIEW. The considered scenario is constituted by a biconical dipole

placed 0.5 m far from a metallic panel. The obtained frequency and time

responses are in very good agreement with simulations.

The proposed model has been used for the feasibility study of a UWB

radar. Once the system specifications (goals) are fixed in terms of bandwidth,

139

EIRP, SNRoutdB, etc., the model parameters have been optimized to fulfill

the goals.

Finally, the various system blocks have been designed.

With reference to the UWB sources, various configurations have been

designed and realized in hybrid technology by using RO4003 substrate and

step recovery diodes. The time behaviors of the source output voltages have

been evaluated with a good agreement between simulation and measurement

results.

A novel directional planar UWB antenna has been presented. Simula-

tions results show that the antenna has a -10 dB bandwidth in the UWB

frequencies. Time domain performances of this antenna have been inves-

tigated showing a very good fidelity factor and an almost constant group

delay. A prototype of the antenna has been realized on RO4003 substrate

and the return loss has been measured, obtaining a good agreement between

simulations and measurements.

In order to evaluate the complex values of the man radar cross section,

the visible human model has been considered. Moreover, two novel human

models, simulating a normal (tidal breath - TB) and a deep breath (DB)

have been implemented. The SRRCS absolute value does not change signifi-

cantly among the three considered models, while SRRCS phase angle changes

considerably.

The design of the receiver, based on the range gating technique, has been

conducted. The receiver utilizes as input the signal scattered by the human

body during respiration and as strobe signal a delayed replica of the source

signal.

Simulation have been performed on a prototype realized with Schottky

diodes. The simulation results point out the ability of the UWB receiver to

convert short time delay among the received signals in voltage variations.

A further study has been performed to evaluate the feasibility of heartbeat

monitoring with a UWB radar system using a wearable antenna. An heart

model has been inserted inside a dispersive box model of the thorax and a

small antenna manufactured on RT6010 substrate has been placed in front

of the thorax model. Numerical simulations showed the possibility to reveal

140

the heart movements with the considered wearable system.

As future work, the whole system will be realized on a single substrate

and tested for breath activity monitoring.

New additional human models (man, woman, and child) will be consid-

ered for the SRRCS computation, to better test the entire system.

The non-invasive monitoring by ultra wideband radar of respiratory ac-

tivity of people inside a spatial environment will be investigated within the

NIMURRA project, approved by the Italian Space Agency (ASI), in which

the Department of Information Engineering, Electronics and Telecommuni-

cations (DIET), where my thesis work has been developed, is involved.

141

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UWB Radar System for Breath Activity Monitoring