August 8, 2006 ©KP/CWINS

Precision Indoor Personnel Location and Tracking for Emergency ResponsesTechnology Workshop, Aug 7-8, 2006

CWINS

Multipath and Robust Precise Indoor GeolocationMultipath and Robust Precise Indoor GeolocationMultipath and Robust Precise Indoor GeolocationMultipath and Robust Precise Indoor Geolocation

Kaveh Pahlavan

August 8, 2006 ©KP/CWINS

Lessons from the past

� In the second half of the 1990’s DARPA started the SUO/SAS project for Urban and Indoor location aware networking, VC funded a few start up companies such as PinPoint, and indoor geolocationresearch started.

� In 2000 indoor WiFi localization – Commercial: Newbury Networks and Ekahau

� In 2003 UWB localization for WPANs– Commercial: IEEE 802.15.3

– ARL: SBIR won by MSSI and IWT

� In 2004 localization for sensor networks

� In 2005 outdoor localization with GPS alternatives– Commerce: WiFi positioning in outdoor areas

(Skyhook)

– Military: Signals of opportunity for disaster recovery (DARPA, Rosum)

Source: DARPA web site

August 8, 2006 ©KP/CWINS

CWINS experiences

� Urban Geolocation System Analysis and Demonstrator with TASC/Litton (DARPA SUO/SAS) -1997– Measurement campaign in multiple buildings at 60, 90, 500 and 1000MHz

– Observation of large errors caused by undetected direct path conditions

� Wireless Indoor Geolocation and Vo-IP-v6 with University of Oulu, Finland (Nokia, Sonera, TEKES, Finland) – 1999– TOA localization using HIPERLAN-2 OFDM WLAN signals

� Indoor Geolocation Science for 4G Wireless Networks (NSF) – 2001– Developed a framework for modeling the distance measurement error for traditional algorithms

– Discovered the effectiveness of the super-resolution algorithms for TOA estimation

� Innovative Methods for Geolocation and Communication with UWB Mobile Radio Networks, with IWT (ARL SBIR) - 2004– UWB measurements and modeling for indoor geolocation in different buildings

– Performance evaluation of traditional algorithms using these models

� Innovative Indoor Geolocation Using RF Multipath Diversity – with Draper Laboratory – 2005– Robust navigation in the absence of direct path

– Channel modeling for dynamic behavior of channel

In addition, CWINS has had continual interactions with PinPoint, InTrak, Ekahau, PanGo and Skyhook

August 8, 2006 ©KP/CWINS

0 50 100 150 200 250 300 3500

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 .7

0 .8

0 .9

1

0 50 100 150 200 2 50 300 3 500

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 .7

0 .8

0 .9

1

0 50 100 150 200 2 50 3 00 3500

0.1

0 .2

0 .3

0 .4

0 .5

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0 .9

1

0 50 1 00 1 50 200 250 3 00 3500

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Fc = 1 GHz / BW = 200 MHz

Peak value = -59.9 dB

Fc = 500 MHz / BW = 200 MHz

Peak value = -59.0 dB

Fc = 90 MHz / BW = 100 MHz

Peak value = -34.5 dB

Fc = 60 MHz / BW = 50 MHz

Peak value = -31.3 dB

RF Propagation Measurements for SUO/SAS

J. Beneat, K. Pahlavan, and P. Krishnamurthy, "Radio Channel Characterization for Geolocation at 1 GHZ,

500MHZ, 90 MHZ, and 60 MHZ In SUO/SAS", MILCOM99, Atlantic City, NJ, November 1999

August 8, 2006 ©KP/CWINS

Super Resolution Techniques for

TOA Estimation

Estimation of

channel frequency

response

Super-resolution

algorithm

Detection

of TOA

Received

signal )(ˆ fH

Pseudospectrum

)(τSEstimate

of TOA

0τ

0 100 200 300 400 500 6000

0.2

0.4

0.6

0.8

1

noi: 14 1 160 40

delay (ns)

Normalized time-domain response

IFTDSSSMUSIC

A sample result:

Note:

IFT: uses Hanning window

DSSS: uses raised cosine pulses

X. Li and K. Pahlavan, “Super-resolution TOA estimation with diversity for indoor geolocation”, IEEE Trans on Wireless

Comm. Dec. 2003

X. Li, “ Super-resolution TOA Estimation with Diversity for Indoor Geolocation”, PhD Dissertation, CWINS, WPI, 2003

N. Alsindi, X. Li, K. Pahlavan, “Analysis of TOA estimation using wideband measurements of indoor radio propagations,”

accepted for publication in IEEE Transactions on Instrumentation and Measurement, 2006.

August 8, 2006 ©KP/CWINS

� The first path is not detectable by measurement

system - Undetected Direct Path (UDP) [Pah98]

� Measurement bandwidth is not wide enough to

distinguish the first few paths from each other [Ala03]

Limitations on Bandwidth Undetected Direct Path

Two Sources of Error

[Pah98] K. Pahlavan, P. Krishnamurthy and J. Beneat, “Wideband Radio Propagation Modeling for Indoor Geolocation

Applications”, IEEE Communications Magazine, April 1998.

[Ala03] B. Alavi and K. Pahlavan, “Bandwidth Effect on Distance Error Modeling for Indoor Geolocation,” 14th Annual IEEE

International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC’03), Beijing, China, September 7-10,

2003.

August 8, 2006 ©KP/CWINS

UWB Measurements for IWT/ARL

0 20 40 60 80 100 120 140 160 180 2000

0.5

1

1.5

2

2.5

x 10-5

← 40.7ns, -106.6dB

← 55.3ns, -92.8dB

← 40.5ns

time (ns)

Amplitude

. \WPI\AK1F\tA2\rE\re6_m1.s1p, (40.7ns, -106.6dB)

0 20 40 60 80 100 120 140 160 180 2000

1

2

3

4

5

6

7

8

9

x 10-5

← 45.8ns, -85.1dB

← 51.1ns, -82.2dB

← 40.5ns

time (ns)

Amplitude

.\WPI\AK1F\tA2\rE\re6_m1.s1p, (45.8ns, -85.1dB)

Bandwidth = 3GHz Bandwidth = 500MHz

0 50 100 150 200 250 3000

1

2

3

4

5

6

x 10-6

← 99.6ns, -112.4dB

← 155.1ns, -106.1dB

← 79.2ns

time (ns)

Amplitude

.\WPI\AK3F\tA0\rC\rc7_m1.s1p, (99.6ns, -112.4dB)

0 50 100 150 200 250 3000

0.5

1

1.5

2

2.5

x 10-5

← 92.7ns, -104.7dB

← 123.6ns, -93.7dB

← 79.2ns

time (ns)

Amplitude

.\WPI\AK3F\tA0\rC\rc7_m1.s1p, (92.7ns, -104.7dB)

LNAVector

Network

Analyzer

B. Alavi, N. Alsindi, K. Pahlavan, “UWB Channel Measurements for Accurate Indoor Localization,”

Military Communications Conference Proceedings, MILCOM 2006, Washington, DC, 23-25 October 2006.

August 8, 2006 ©KP/CWINS

Distance Measurement Error Modeling

Total 638 OLOS

Points

Bandwidth = 50 MHz Bandwidth = 100 MHz Bandwidth = 500 MHz

Scatter Plots of Distance Error for Different Bandwidths (OLOS)

UDP Cases (bandwidth independent)

Bardia Alavi and Kaveh Pahlavan, “Modeling of the TOA based Distance Measurement Error Using

UWB Indoor Radio Measurements” IEEE Communications Letters, April 2006.

Bardia Alavi, “Distance Measurement Error Modeling for Time-of-Arrival Based Indoor

Geolocation”, PhD Dissertation, CWINS, WPI, April 2006.

August 8, 2006 ©KP/CWINS

Performance Evaluation Laboratories

� Elements of an RF laboratory

– Channel simulators or a defined route

– Interface to products

– Isolated environment

� Examples

– Testbed using a defined path

– Ekahau localization testbed using Elektrobit channel

simulator

– Azimuth isolated testbed

August 8, 2006 ©KP/CWINS

Example: Comparisons Using a Specific Route

AP1

AP2

AP3

User

50 m

30 m

B1

B2

A. Hatami, and Kaveh Pahlavan, " Comparative statistical analysis of indoor positioning using empirical

data and indoor radio channel models," Consumer communications and networking conference, 2006

August 8, 2006 ©KP/CWINS

TOA vs RSS

0 10 20 30 40 50 600

5

10

15

20

25

30

35

40

X [m]

Y [m

]

Indoor Position Using Least Square TOA (B.W.= 500 MHz)

Track of Movement

L.S. TOA Estimation

AP locationsAP3

AP1

AP2

0 10 20 30 40 50 600

5

10

15

20

25

30

35

40

X [m]

Y [m

]

Indoor Position Using Maximum Likelihood RSS (B.W.= 25 MHz)

Track of Movement

Max. Like. RSS Estimation

AP locationsAP3

AP2

AP1

August 8, 2006 ©KP/CWINS

WiFi vs UWB

Localization RMS Error (DDP)

0

2

4

6

8

10

12

14

25 MHz 500 MHz ∞

Receiver Bandwidth

Err

or[

m]

CN-TOAG

LS TOA

Stat. RSS

RT-CN

Localization RMS Error (UDP)

0

5

10

15

20

25 MHz 500 MHz ∞

Receiver Bandwidth

Error[

m]

CN-TOAG

LS TOA

Stat. RSS

RT-CN

August 8, 2006 ©KP/CWINS

Real-Time Channel Simulator

� Active channel simulator

� Provides simulation of up to 8 unidirectional channels

� Simulates multipath behavior using a tapped delay line

� Can be utilized for a wide range of wireless devices (e.g. cellular, WLAN, sensors, RFIDs, etc.)

� Frequency specifications:

– Bandwidth of 70 MHz

– Frequency range from 350MHz to 6 GHz

Purchased with DoD grant

(Elektrobit PROPSim C8)

August 8, 2006 ©KP/CWINS

Example: Testbed for Ekahau Deployment

Server and

EKAHAU

softwareRay tracing and

Display

PROPSim channel

simulator

Access

points

M. Heidari and K. Pahlavan, Performance Evaluation of Indoor Geolocation Systems Using PROPSim Hardware and Ray Tracing

Software, IWWAN’04, Oulu, Finland, May 2004.

August 8, 2006 ©KP/CWINS

Deployment Analysis

August 8, 2006 ©KP/CWINS

Performance Results

August 8, 2006 ©KP/CWINS

RF Isolated Environment

� Cabled WLAN test solution

� Provides high levels of isolation from the surrounding environment

� Allows for repeatability

� Full automation and remote access capability

� Various test setups possible including range, roaming, and VoIP

Purchased with NSF grant

(Azimuth Systems

801W)

August 8, 2006 ©KP/CWINS

Example: Testbed for WiFi Coverage

L.T. Metreaud and K. Pahlavan, "RF Isolated Real-Time Multipath Testbed for Performance Analysis of WLANs,"

presented at the 40th Annual Conference on Information Sciences and Systems, Princeton, NJ, 2006.

August 8, 2006 ©KP/CWINS

Testbed Equipment for Coverage

August 8, 2006 ©KP/CWINS

Sample RSSI of WiFi

Average RSSI vs. Linear Distance

-100

-90

-80

-70

-60

-50

-40

0 500 1000 1500 2000 2500 3000 3500 4000

Linear Distance [m]

RSSI [dBm]

August 8, 2006 ©KP/CWINS

Conclusions

� Multipath poses a serious challenge to design

of robust indoor geolocation systems

� There are a number of candid technologies,

we need testbeds to compare their

performances

� Channel measurement and modeling is

essential for understanding of the behavior of

the channel to implement meaningful

testbeds for performance evaluation

August 8, 2006 ©KP/CWINS

For details of our projects and publications see:

www.cwins.wpi.edu