SYNTHETIC IMPULSEAND APERTURERADAR (SIAR)

SYNTHETIC IMPULSEAND APERTURERADAR (SIAR)A NOVEL MULTI-FREQUENCYMIMO RADAR

Baixiao ChenXidian University, P. R. China

Jianqi WuHefei Association for Science and Technology, P. R. China

This edition first published 2014© 2014 National Defense Industry Press. All rights reserved.

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Library of Congress Cataloging-in-Publication Data

Synthetic impulse and aperture radar (SIAR) : a novel multi-frequency MIMO radar /Baixiao Chen and Jianqi Wu.

pages cmIncludes bibliographical references and index.ISBN 978-1-118-60955-2 (cloth)1. Synthetic aperture radar. 2. MIMO systems. I. Chen, Baixiao. II. Wu, Jianqi.TK6592.S95S974 2014621.3848′5–dc23

2013030811

ISBN: 978-1-118-60955-2

Set in 11/13 Times by Laserwords Private Limited, Chennai, India

1 2014

Contents

About the Authors xiii

Preface xv

Acknowledgments xix

1 Introduction 11.1 Development of Modern Radar 11.2 Basic Features of SIAR 31.3 Four Anti Features of SIAR 4

1.3.1 Anti-stealth of SIAR 41.3.2 Anti-reconnaissance of SIAR 61.3.3 Anti-ARM of SIAR 61.3.4 Anti-interference of SIAR 8

1.4 Main Types of MIMO Radar 91.5 SIAR and MIMO Radar 111.6 Organization of This Book 12

References 15

2 Radar Common Signal Waveform and Pulse Compression 172.1 Mathematical Form and its Classification of Radar Signal 17

2.1.1 Signal Mathematical Form 172.1.2 Radar Signal Classification 22

2.2 The Ambiguity Function and Radar Resolution 232.2.1 Definition and Properties of the Ambiguity Function 232.2.2 Radar Resolution 282.2.3 The Ambiguity Function of a Constant-Frequency Pulse 33

2.3 FM Pulse Signal and its Pulse Compression 382.3.1 Linear Frequency Modulation (LFM or Chirp) Pulse Signal 402.3.2 NLFM Pulse Signal 462.3.3 LFM Pulse Compression 502.3.4 Range-Doppler Uncertainty Principle of LFM 54

vi Contents

2.4 Phase Coded Pulse Signal and its Processing 562.4.1 The Waveform and Its Characteristic of Binary Phase Coded

Signals 572.4.2 Barker Codes 602.4.3 M-sequence Coded Signal 632.4.4 Pulse Compression for a Phase Coded Signal 672.4.5 The Effect of Doppler on a Phase Coded Signal 692.4.6 Comparison of an LFM Signal with a Phase Coded Signal 71

2.5 Stepped-Frequency Pulse Signal and its Processing 732.5.1 Stepped-Frequency (Hop-Frequency) Pulse Signal 732.5.2 FM Stepped Pulse Signal 772.5.3 Stepped-Frequency Waveform Synthesis Processing 78

2.6 Orthogonal Waveform 842.6.1 The Orthogonal Waveform 842.6.2 Orthogonal Binary Phase Coded Sequence Design Based on the

Genetic Algorithm 85

2.7 MATLAB® Program List 95References 102

3 System Design of SIAR 1033.1 Introduction 1033.2 Principles of SIAR 104

3.2.1 Orthogonal Frequency-Coded Signals 1043.2.2 Concepts of Impulse Synthesis and Aperture Synthesis 1063.2.3 Spatial-Temporal 3D Matched Filtering 1073.2.4 Synthesis of the Transmit Beam 109

3.3 Synthesis of Transmit Pulse and Aperture 1133.3.1 Wideband Signal Model of SIAR 1133.3.2 Impulse Synthesis in Time and Frequency Domains 1153.3.3 Impulse Synthesis in the Time Domain 1163.3.4 Impulse Synthesis in the Frequency Domain 1173.3.5 Sampling Loss and its Compensation 119

3.4 4D Ambiguity Function of SIAR 1203.4.1 Ambiguity Function of a Common Radar 1203.4.2 4D Ambiguity Function of SIAR 1213.4.3 Analysis of 4D Resolution Capability 123

3.5 Radar Equation of SIAR and its Characteristics 1263.5.1 SIAR Radar Equation and Phased Array Radar Equation 1273.5.2 Energy Utilization Ratio of SIAR 1283.5.3 LPI Performance of SIAR 1293.5.4 Compare SIAR with PAR 130

Contents vii

3.6 Experimental System of SIAR 1333.6.1 Antenna Subsystem 1343.6.2 Transmitting Subsystem 1353.6.3 Receiving Subsystem 1353.6.4 Frequency Synthesis Subsystem 136

3.7 Gain and Phase Calibration of SIAR 1373.8 Experimental Results of SIAR 1423.9 SIAR with Large Random Sparse Array 1453.10 Brief Summary 147

3.11 MATLAB® Program List 1483.11.1 1D Ambiguity_Function of SIAR 1483.11.2 2D Ambiguity_Function of SIAR 150References 152

4 Waveform and Signal Processing of SIAR 1554.1 Introduction 1554.2 Waveform and Signal Processing Flow of SIAR 1564.3 Application of LFM in SIAR 1604.4 SIAR Performance Analysis of Pulse Compression based on Phased

Codes 1634.5 Pulse-to-Pulse Frequency Code Agility and its Signal Processing Flow 1704.6 Group-to-Group Frequency Code Agility and its Signal Processing 1794.7 Brief Summary 180

4.8 MATLAB® Program List 1814.8.1 Simulation Program of SIAR in Frequency Code Nonagility 1814.8.2 Simulation Program of SIAR in Frequency Code Agility 183

Appendix 4A Deductions of Some Equations in This Chapter 185References 189

5 Long-Time Coherent Integration of SIAR 1915.1 Introduction 1915.2 Features and Faults of Long-Time Coherent Integration of SIAR 192

5.2.1 Number of Coherent Integration Pulses is Limited by theBandwidth of Transmitting Signals 193

5.2.2 Variation of Doppler Frequency during Long-Time Motion ofthe Target 194

5.2.3 Time Limitation of a Target Passing through a Resolution Bin 1965.3 Long-Time Coherent Integration Based on Motion Compensation and

Time-Frequency Analysis 1975.4 Long-Time Coherent Integration Based on Pulse Synthesis of Stepped

Frequency 2035.4.1 Pulse Synthesis of a Stepped-Frequency SIAR 203

viii Contents

5.4.2 Influence of Target Motion on Stepped-Frequency Synthesis 2075.5 Computer Simulation 2105.6 Brief Summary 213

References 213

6 Digital Monopulse Tracking Technique of SIAR 2156.1 Overview of the Monopulse Tracking Technique 2156.2 Tracking Processing and Signal Model of SIAR 2186.3 Precision Measurement of the Target Range 220

6.3.1 Frequency Diversity Method (Positive and Negative FrequencyImpulse Synthesis Method) 221

6.3.2 Lead-delay Impulse Synthesis Method 2246.3.3 Accuracy of Range Measurement 2276.3.4 Computer Simulation 227

6.4 Measurements of the SIAR Target’s Direction 2306.5 Measurement of Doppler Frequency 2356.6 Brief Summary 238

References 239

7 Coupling and Decoupling between Range and Angle 2417.1 Introduction 2417.2 Coupling Influence of Angular Error on Range Measurement 2427.3 Coupling Influence of Range Quantization Error on Angle Measurement 2447.4 Range-Angle Coupling Analysis Based on the Fisher Information

Matrix 2477.5 Frequency Code Optimization and Three-Dimensional Decoupling

Analysis 2497.6 Computer Simulation 2557.7 Brief Summary 256

References 257

8 Target Detection and Tracking in SIAR under Strong Jamming 2598.1 Introduction 2598.2 Anti-Jamming Measures of the SIAR System 2608.3 Adaptive Nulling and Computer Simulation for the Phased Array Radar 261

8.3.1 Digital Beamforming for the Phased Array Radar 2618.3.2 Adaptive Digital Beamforming for the Phased Array Radar 2668.3.3 The Optimal Adaptive Beamforming Criteria for the Phased

Array Radar 2688.3.4 Computer Simulation of ADBF 272

8.4 Adaptive Nulling and Computer Simulation for SIAR 2778.5 Target Range Measurement in SIAR Under Active Jamming 2818.6 Target Direction Measurement in SIAR Under Active Jamming 283

Contents ix

8.7 Performance Analysis of Sidelobe Cancelation in SIAR 2858.7.1 Interference Cancelation in the Sparse Circular Array 2868.7.2 Adapting Sidelobe Interference Cancelation Measurements in

SIAR 2908.7.3 Computer Simulation 291

8.8 Summary 292

8.9 MATLAB® Program List 294References 296

9 Effects of Array Error on SIAR Tracking Accuracy 2979.1 Introduction 2979.2 Effect of Amplitude and Phase of the Array Element on Tracking

Accuracy 2989.2.1 Signal Model 2989.2.2 Effect of Amplitude–Phase Error on Monopulse Angle

Measurement Accuracy 2999.2.3 Effect of Amplitude–Phase Error on Range Accuracy 3029.2.4 Computer Simulation 303

9.3 Influence of Channel Mismatch on Tracking Accuracy 3039.3.1 Signal Model of Channel Mismatch 3049.3.2 Influence of Channel Mismatch on Tracking Accuracy of SIAR 3079.3.3 Computer Simulation 311

9.4 Influence of Orthogonal Channel Imbalance on Tracking Accuracy 3129.4.1 Signal Model 3129.4.2 Influence of I/Q Component Imbalance on Tracking Accuracy 3139.4.3 Computer Simulation 316

9.5 Summary 317References 318

10 Bistatic Synthetic Impulse and Aperture Ground Wave RadarExperimental System 319

10.1 Introduction 31910.2 The Composition and Characteristics of the Test System 321

10.2.1 Transmitting Antenna Subsystem 32210.2.2 Transmitter (Power Amplifier) 32310.2.3 Receiving Subsystem 32310.2.4 Digital Frequency Source Subsystem 32710.2.5 Characteristics of the System 330

10.3 The Parameter Design of the Waveform of the Bistatic SyntheticImpulse and Aperture Ground Wave Radar 33110.3.1 The Selection of the FM (Sweep) Cycle Tm 333

x Contents

10.3.2 The Sweep Frequency Bandwidth and the FrequencyModulation Rate 333

10.3.3 The Pulse Repetition Cycle Tr and the Pulse Width Tp 33310.3.4 The Selection of the Working Frequencies {fl} 335

10.4 Working Principles of the Bistatic Synthetic Impulse and ApertureGround Wave Radar 33610.4.1 The Signal Processing Flow of the Radar 33610.4.2 Extraction of the Transmitting Synchronous Information 33710.4.3 The Transmitting Synthesizing Process 34210.4.4 Coordinate Transformation and Target Positioning 345

10.5 Sea Clutter Characteristic of the Bistatic HF Ground Wave Radar 34710.5.1 Geometric Relationship of the Bistatic Ground Wave Radar

System 34710.5.2 Sea Clutter Characteristics of the Bistatic Radar in the Moving

Platform 34910.6 Results of Real-Data Processing 359

10.6.1 Experimental Results for the Static Receiving Station 35910.6.2 Experimental Results for the Moving Receiving Station 364

10.7 Brief Summary 364References 366

11 Microwave Sparse Array Synthetic Impulse and Aperture Radar 36911.1 Introduction 36911.2 Transmit Signal Waveform of MSA-SIAR 37011.3 The Array and its Optimization of MSA-SIAR 372

11.3.1 Introduction of the Genetic Algorithm 37611.3.2 Optimizing the Array Pattern Using the Modified Genetic

Algorithm 37811.3.3 Simulation Results of Array Optimization 380

11.4 The Signal Pre-processing Method Based on Digital Dechirp Processing 38211.4.1 LFM Signal Model 38211.4.2 Channel Separation Pre-processing Method 38311.4.3 Velocity Compensation Precision Analysis 38511.4.4 Selection of the Number of Coherent Integration Periods M 38611.4.5 Signal Processing Flow 386

11.5 MSA-SIAR Based on IDFT Coherent Synthesis 38711.5.1 Simulation 1 38911.5.2 Simulation 2 389

11.6 Spatial Domain Synthetic Bandwidth Method of MSA-SIAR 39211.6.1 Introduction of the Conventional Synthetic Bandwidth Method 39211.6.2 Spatial Domain Synthetic Bandwidth Method 39311.6.3 Spectrum Concatenating Algorithms 396

Contents xi

11.6.4 Analysis of Moving Targets 39711.6.5 Comparison of the Conventional Synthetic Bandwidth Method 39811.6.6 Simulation Results 398

11.7 Summary 400References 401

Bibliography 405

Index 409

About the Authors

Baixiao Chen was born in Susong, Anhui, China, in 1966.In 1987, he graduated from Anhui University of Tech-nology. In 1994 and 1997, he received an MS degree incircuit and system and a PhD in signal and informationprocessing at Xidian University, China. He is currently aProfessor and Academic Leader of Signal and Informa-tion Processing and Doctoral Tutor in National Labora-tory of Radar Signal Processing, Xidian University. Hiscurrent research interests include the synthetic impulseand aperture radar (SIAR), array signal processing, andnew radar system design. He has been in charge of more

than 20 radars and has published over 140 articles, in which more than 90 papers areindexed by SCI and EI.

Jianqi Wu was born in Yibin, Sichuan, China, in 1966.In 1987 and 1990, he received a BS degree at BeijingUniversity of Aeronautics and Astronautics and an MSdegree at the University of Electronic Science and Tech-nology respectively. He is the vice-director and directorof Science and Technology Commission of CECT 38,the vice-president of Hefei Association for Science andTechnology, a member of GAD scout measurement pro-fessional group, and the director of Chinese Institute ofElectronics. He has been working in radar for more than20 years. He was in charge of the key national defense

advance research project “Sparse Array Synthetic Impulse and Aperture Radar Exper-imental System” and several key model projects. He is the author of over 10 jour-nal articles. He has won a first class National Scientific and Technological ProgressAward, two second class National Scientific and Technological Progress Awards, afirst class National Defense Scientific and Technological Progress Prize, and an out-standing contribution award of Science and Technology of Hefei.

Preface

Modern wars are driving the development of stealth technology, anti-radiationmissiles (ARM), electronic countermeasures (ECM), and low-altitude penetration.These are presenting new challenges and higher requirements for the modern radar.Since it is difficult for the conventional radar to deal with new challenges, a seriesof advanced technologies have been employed to develop a new radar system.Especially, the meter-wave radar has significant advantages for anti-stealth.

The synthetic impulse and aperture radar (SIAR) is a new kind of meter-wavedistributed radar with capability and performance of anti-stealth, low probability ofinterception, ARM, anti-interference, four-dimensional parameter estimate and highaccuracy. The SIAR provides an effective approach to detect and track stealth air-crafts and other low-altitude targets for early warning and guidance. The SIAR hasovercome the disadvantage of low resolution in the meter-wave radar by adopting asparse separated antenna. Each transmitting antenna is omnidirectional and radiatesan orthogonal frequency-coding signal, so that the entire space can be symmetricallycovered. The transmitting beam and receiving beam is formed at the receiving stationvia signal processing. The SIAR has many differences from the conventional radar forthe special system and operation mode, which rises some new problems. The SIARis a novel multifrequency multiple-input multiple-output (MIMO) radar.

This book provides a systematic description of the working principle, signal pro-cessing procedures, target measurement techniques, and experimental results of theSIAR in compliance with engineering practice. In addition, the synthetic impulse andaperture can also be applied in the radar of the high-frequency (HF) band and themicrowave band. The coast–ship bistatic HF surface wave SIAR experimental systemand the microwave sparse-array SIAR have also been described.

The book contains eleven chapters and is organized as follows. Chapter 1 byBaixiao Chen and Jianqi Wu gives an introduction to the SIAR, including the basiccharacter and the capability of anti-stealth, anti-ARM, and anti-interference. Chapter2 by Baixiao Chen and Wei Zhu gives the common radar waveform, including theFM pulse signal, phase coded signal, stepped-frequency pulse signal, and orthogonalwaveforms. The mathematical form of the radar signal, the ambiguity function, andthe corresponding processing methods are emphasized. Chapter 3 by Jianqi Wu,Baixiao Chen, and Kai Jiang is used as the basis for the following chapters. It presents

xvi Preface

the operating principle and system structure of the SIAR. Chapter 4 by BaixiaoChen and Jianqi Wu describes the waveforms of SIAR and the corresponding signalprocessing procedures. Chapters 5 to 9 are written by Baixiao Chen. In Chapter 5,long-time coherent integration techniques of the SIAR are discussed. Accordingto the features and open questions of long-time coherent integration, two kinds oflong-time coherent integration algorithm are proposed. One is based on motioncompensation and time-frequency analysis; the other is based on stepped-frequencyimpulse synthesis. Detailed derivations of digital mono-pulse tracking, used forprecision measurement of the target (including distance, azimuth, elevation, andDoppler frequency 4D parameters with the transmitting aperture and receiving aper-ture simultaneously), is presented in Chapter 6. Chapter 7 is dedicated to describingcoupling between the range and angle in the SIAR. The influence of coupling andthe method of decoupling is analyzed. In order to overcome the coupling effectamong range, azimuth, and elevation, an optimized frequency-coding criterion ofthe transmitting signals is studied. Chapter 8 treats the detection and tracking of thetarget under a background of strong interference. The adaptive interference nullingtechniques constitute the main topic. Also, the effects of the aperture–bandwidthproduct, gain-phase errors, and quantizing noise in the analog/digital (A/D) converterto a large circular-aperture SIAR are quantitatively analyzed. Chapter 9 deals withthe impact on tracking accuracy of the SIAR caused by array perturbation, includinggain-phase errors, channel mismatch, and unbalance among orthogonal channels.Chapter 10 by Baixiao Chen and Duofang Chen contains the bistatic surface-wavesynthetic impulse and aperture radar (BSW-SIAR) experimental system. Thisincludes the operating principle and experimental results of this over-the-horizon(OTH) radar. The microwave sparse array synthetic impulse and aperture radar isdemonstrated in detail in Chapter 11 by Baixiao Chen and Minglei Yang.

In fact, the SIAR is a typical kind of MIMO radar. The MIMO radar also uses theconcept of SIAR. Researchers at Oxford University gave the following appraisement:“MIMO radar is inspired mainly by the synthetic impulse and aperture radar (SIAR).… ” The presenters of the “statistical MIMO radar” in the Research Institute of theState University of New Jersey and Bell Labs described it as follows: “Recently, a newand interesting concept in array radar has been introduced by the synthetic impulseand aperture radar (SIAR) . . . .” Therefore, publication of this book should play apositive role in the promotion for the research of the MIMO radar.

The intention of this book is to make readers systematically, comprehensively,deeply understand the basic concept, working principles, operation mode, and sig-nal processing procedures of the SIAR, and the differences from conventional radars.The design thoughts, development methods, and some special considerations of theSIAR are also included.

The author has been working on system design and signal processing of radar in thepast 20 years with professional theories and much engineering experience. More than80 papers about the SIAR have been published. This book is a summary of 20 years ofresearch on the SIAR. It is hoped that this book will be a useful reference for working

Preface xvii

engineers as well as a textbook for students learning about the SIAR, MIMO systems,and digital radars analysis and design. We give many MATLAB codes in this bookfor the reader to better understand the SIAR and MIMO radar.

I wish to thank academicians Erke Mao, Xiaomo Wang, and Manqing Wu of theChinese Academy of Engineering, Zhen Bao of the Chinese Academy of Sciences,Professor Yingning Peng of Tsinghua University, and Professor Shouhong Zhang ofXidian University. I would also like to thank the SIAR research group founded by No.38 Research Institute of CETC and Xidian University.

I am grateful for academicians Erke Mao, Manqing Wu, and Professor YingningPeng for recommendation of this book for the Fund of National Defense Science.

The original motive for writing this book was to make a contribution to thedevelopment of radar. As a level of limited mistakes and deficiencies are inevitable,researchers are encouraged to make criticisms.

Finally, I thank the Fund of National Defense Science and Technology Book andall editors.

Acknowledgments

I am grateful to Xidian University and National Laboratory of Radar Signal Processingfor supplying me with such a perfect working condition and good academic circum-stances. I should give my thanks to the No. 38 Research Institute of China ElectronicsTechnology Group Corporation (CETC) for helping us to accomplish the project.

I would like to extend my sincere thanks to Professor Li Jian for many valuablecomments.

I would also like to express my sincere appreciation to many friends and colleagues,Dr Wang Zhongde, Dr Ye Wei, and Dr Ma Zhangzheng, for their creative discussionand enormous help.

My thanks also go to my students Zhu Wei, Zheng Guimei, Wang Yi, GaoLongchao, Lu Jiazhan, Wang Yu, Chen Genhua, Guo Weina, Zheng Qiaozhen, andXu yebin, who did some of the translation work and revised most of the figures inthis book. I am also thankful for the help from Chen Duofang, Yang Minglei, andQin Guodong; they studied a lot about what is discussed in the book.

Finally, I would like to take this opportunity to thank many people who helped tomake this book possible. My deepest gratitude goes to my family; without their careand support, this book would have been nearly impossible. Most of all, I am thankfulto my wife, Xu Hui, for her love and support, and my son, Chen Runkang, for hissweet smiles.

Chen BaixiaoJuly 5, 2013

1Introduction

1.1 Development of Modern Radar

With the development of microelectronics, very large scale integrated converters(VLSICs), new materials, and advanced productive technologies, modern radartechniques have progressed dramatically. Major development trends in the modernradar are given as follows:

1. Digitization. Digitization of the modern radar is not only represented bysignificantly improved speed of radar signal processing as a result of the rapidlydeveloped VLSICs but also radio frequency (RF) digitization. Indeed, phaseshifters in conventional phased array radars are now gradually being replaced bydirect digital synthesizers (DDSs). Due to the rapid development of DDSs, theycan directly generate RF excitation signals and send them to the power amplifierin a radar transmitter. That is to say, RF excitation signals in different initialphases directly generated by DDSs in various channels are sent respectively toeach transmitter to amplify their power before being sent to each antenna. Afterbeing filtered and amplified in digital receivers, RF signals are sampled directlyby high-speed analog-to-digital (A/D) converters. The digital receivers can obtaindigital baseband signals via digital quadrature conversion without using mixers.

2. Integration. To work effectively in modern warfare, various radar techniques andtools, such as pulse compression, adaptive frequency agility, coherent integration,constant false-alarm-rate (CFAR) circuit, low-probability intercept (LPI), polari-metric information processing, spread spectrum, ultra-low sidelobe antenna, multi-ple transmitting waveform design, digital beamforming (DBF) or adaptive digitalbeamforming (ADBF), and sidelobe cancellation (SLC), should be integrated inthe modern radar system.

3. Multifunction. With the rapid improvement of radar techniques, the radar sys-tem is required to have good detecting, tracking, and identifying capabilities for

Synthetic Impulse and Aperture Radar (SIAR): A Novel Multi-Frequency MIMO Radar, First Edition.Baixiao Chen and Jianqi Wu.© 2014 National Defense Industry Press. All rights reserved. Published 2014 by John Wiley & Sons Singapore Pte Ltd.

2 Synthetic Impulse and Aperture Radar (SIAR)

various targets. In addition, it should have the capability of guiding and targetingfor the weapon system. Furthermore, high survivability should be offered in a com-plex electromagnetic environment.

With the development of stealth techniques, anti-radiation missiles (ARMs), elec-tronic countermeasures (ECMs), and low-altitude penetration [1–6], new challengesand higher demands are expected. As traditional radars are incapable of dealing withthese challenges, new countermeasures must be adopted. In order to deal with these“Four Threats,” modern radar is required to employ a series of advanced techniques,such as pulse compression, SLC, and coherent integration. Since stealth aircraft hasbeen successfully applied in recent local wars, anti-stealth techniques have become a“have-to-solve” issue.

Current stealth technologies are mainly focused on structure stealth design,impedance loading, absorbing material coatings, and absorbing penetrating materialsto reduce radar cross-section (RCS). These techniques are widely acknowledgedas useful measures for centimeter wave radars. However, it has little impact forelectromagnetic waves of longer wavelengths (such as meter waves). Since the RCSof a target is related to the radar wavelength with the form RCS= n𝜆 [7], where ndepends on the geometrical shape of the target and has a value between 0 and 2, and 𝜆is the wavelength. At the international conference on radar systems in 1985, Moraitisanalyzed the influence of radar frequency on the detection of stealth targets. Theresults show that the RCS of stealth aircraft is higher at the metric band than at theS-band by 15–30 dB. Meanwhile, the impedance loading cannot be carried out sincethe metric band is the resonance region of the airframe. Absorbing material coatingsare influenced by frequency characteristics. Currently, the effective frequency isbetween 1 and 20 GHz, with the coating thickness lying between 1/10 and 1/4wavelength. For the metric wave, it is impossible for the coating thickness to be upto an order of 10 cm. Therefore, the absorbing material coating is not a threat to themetric radar. The absorbing penetrating materials also cannot be applied effectivelyin the metric wave due to the frequency characteristics of the materials. Thus, themetric wave radar has a good capability in detecting stealth targets.

However, traditional metric radars have difficulties in meeting the requirements ofmodern warfare due to their wide beams, poor positioning accuracy, and especiallytheir inability to track and guide multiple targets. In recent years, radar researchersare trying to improve the performance of resolution, low-altitude detection, anti-jamming, multiple target detection with the metric radars. However, these effortsare only improvements to the traditional radar system, so it is difficult to meettheir desired purposes. Only the Synthetic Impulse and Aperture Radar (SIAR,“RIAS” in French) invented by ONERA in the late 1970s was an entirely new four-dimensional (range, azimuth, velocity, and elevation) multifunction (surveillance andtracking) radar system [8–15] To overcome the inherent weakness of low angularresolution, the large sparse array is employed in this metric wave radar. Due toits new transmitting signal system and advanced signal processing techniques, the

Introduction 3

isotropic illumination for the whole space can be performed with a large antennaarray, which has strong directivity. Aperture synthesis and impulse synthesis forsignals with large time widths are performed at the same time, so an LPI canbe realized.

1.2 Basic Features of SIAR

The basic concepts of SIAR can be summarized as follows:

1. By encoding the signals of each omnidirectional radiation element, the isotropicradiation of the entire space is ensured with a large antenna array with strong direc-tivity; that is, the beam pattern of the transmit signal is not formed in the spatialdomain.

2. Signal components of each transmitting element are separated in the receiving sys-tem based on their codes. The time delay is calibrated via the elements in the space,and then the signal components are coherently combined again to generate narrowpulses of target echoes, namely the equivalent transmitting beam patterns.

SIAR uses multiple antennas to transmit orthogonal signals with multicarrier fre-quencies. These signals have unique characteristics in wavelength selection, antennatypes, Doppler processing, and beamforming [16]:

1. Operating at the meter wave band. Though the radar with meter wave is suitablefor long-range detection, the angular resolution is low and the accuracy of angularmeasurement is inaccurate due to the limits of the antenna size. Without taking intoaccount the angular resolution, there are many advantages of meter wave radar:(a) Appropriate pulse repetition frequency (PRF) is selected to ensure that range

ambiguity (hundreds of kilometers) and velocity ambiguity (several Machnumbers) can be avoided. In other words, the Doppler processing can berealized with no range ambiguity.

(b) It is difficult to significantly reduce the RCS of targets (whether their shape orcoating) by using stealth techniques.

(c) It is easy to make a filter because of the weak ground clutter and narrow fre-quency spectrum.

(d) It is able to obtain high output power for transmitters at a low cost.(e) It is difficult for enemies to use airborne jammers due to the large antenna

aperture at the meter wave band and electromagnetic compatibility.(f) It has better countermeasures against ARM.

2. Using large sparse array antennas. Low angular resolution is the main obstaclefor meter wave radars. An SIAR experimental system employs 25 transmittingarray elements and 25 receiving array elements, which are uniformly distributedon two circles with diameters of 90 and 45 m respectively. If the wavelength is 3 m,

4 Synthetic Impulse and Aperture Radar (SIAR)

the azimuth angular resolution of the array will be about 1.2∘, which ensures thedesired angular resolution. Meanwhile, taking into consideration the cost and thecomplexity of implementation, the number of antenna elements should not be toolarge. Due to the requirement of detecting targets in all directions, SIAR choosesa large sparse circular antenna array with a limited number of elements.

3. Omnidirectional transmission. Each transmit antenna emit signalssimultaneously at different frequencies to ensure that the radiation energy isuniformly distributed in space and coherent speckles cannot be formed. Compar-atively, the conventional phased array radar operates at the same carrier frequencyso spatial coherent speckles representing the transmitting pattern are formed.

4. Doppler processing. The conventional radar needs to steer the beam. The numberof echo pulses at one beam direction is small so only a limited number of pulses canbe provided to integrate because of the time constraint. Since SIAR does not adoptphysical focusing and beam scanning, and provides a continuous surveillance forthe entire airspace, the coherent integration time theoretically is only determinedby the system coherent performance and target’s velocity. The higher the numberof pulses provided for integration, the higher the resolution achieved via Dopplerprocessing. For general surveillance radars, if the antenna rotates at 6 rpm, the datarate is 10 seconds. For SIAR, if the pulse repetition interval is 3 ms and the numberof integration pulses is 256, the Doppler resolution is 1.3 Hz and the data rate ofeach target is 0.768 seconds. It is far above the level of a general surveillance radar.

5. Transmit beamforming. Namely, the transmit pattern is generated at the receivingend through impulse synthesis processing, and “impulse compression” is carriedout based on the multicarriers.

6. It is able to simultaneously form multiple searching beams covering the wholespatial space and multiple tracking beams to perform the monopulse measurementfor each target. SIAR is particularly suitable for detecting and tracking multipletargets since it incorporates surveillance and tracking as a whole.

7. SIAR is a four-dimensional (4D) radar. It can be used to obtain the range, velocity,azimuth, and elevation of targets.

The most significant technical feature of SIAR is that it can realize nondirectionalemission and form multiple “stacked” beams simultaneously. Therefore, the long-time coherent integration can be achieved simultaneously at all beam directions so asto improve the ability to detect dim targets (especially stealth targets).

1.3 Four Anti Features of SIAR

1.3.1 Anti-stealth of SIAR

Modern radar faces the challenge of targets with very small RCS, such as cruise mis-siles, stealth targets, and reentry InterContinental ballistic missile (ICBM) warheads.

Introduction 5

Improving the radar detection ability has always been a hot topic, and it becomesespecially important with the advancement of stealth techniques. To improve detectionability, it is not enough to increase the transmitted power. This new-style radar prin-ciple, waveform design, and signal processing are also needed.

The general radar usually uses coherent integration techniques or noncoherent inte-gration techniques to improve detection ability, but the number of pulses available forintegration is mainly limited by antenna scanning due to beam scanning. For example,if the radar beamwidth is 2∘, the beam scanning speed will be 6 rpm and the radar rep-etition frequency will be 300 Hz, so the number of integrated pulses is less than 17.For three-dimensional (3D) radars, the number of pulses available for integration ismuch lower. In order to suppress the clutter, sometimes only part of the pulses can beintegrated so the signal-to-noise ratio (SNR) improvement gained through integrationis limited.

Since transmit and receive beamformings are realized through signal processing atthe receiving end, impulse synthesis in SIAR can keep the beam at certain directions(even one direction). Therefore, multiple beams or stacked beams (including trans-mitting beams and receiving beams) can be simultaneously achieved at the receivingend. These beams can even cover the entire spatial space without beam scanning andalways track targets. This is equivalent to the “burn-through” operational mode inconventional radar, though the conventional radar only operates in one direction inthe “burn-through” mode. Since there is no beam scanning in SIAR, the integrationtime is only determined by the target’s velocity and the radar parameters, indepen-dent of the beam scanning time on the target. Therefore, SIAR can obtain a largernumber of coherent integration pulses. Furthermore, the signals with a large time-bandwidth can be used in an SIAR system to increase the average power of trans-mitted signals [16, 17], improving the detection range and resolution capability ofthe radar.

SIAR has two advantages in anti-stealth as follows:

1. The stealth technique has an insignificant influence in the meter wave band.Moraitis has analyzed the impact of signal frequency on external shape stealthtechniques. The results showed that the RCS of stealth targets at the meter waveband is higher than at the S-band by 15–30 dB [5].

2. System sensitivity can be improved via long-time coherent integration; thereforeit is beneficial to the detection of dim targets. Its emission energy is dispersed inspace and the energy is only 1/Ne (Ne is the number of antenna), as much as thedirectivity energy of a conventional radar with the same transmitting power. In the-ory, only Ne pulses are required to compensate for the loss of energy during theomnidirectional transmission, but the number of coherent integration pulses goesup to several hundreds and even several thousands, far more than that of the conven-tional radar. Therefore, the energy can be accumulated via long-time observationto achieve anti-stealth performance.

6 Synthetic Impulse and Aperture Radar (SIAR)

1.3.2 Anti-reconnaissance of SIAR

Before implementing synthetic electronic jamming or transmitting ARM to the radarsystem, it is important to confirm the working state of the radar according to its radia-tion information to implement effective jamming or attack. In order to avoid jammingand attacking, modern radar must have high anti-reconnaissance performance. In thisrespect, SIAR is mainly characterized by Chen [16]:

1. Since SIAR adopts omnidirectional radiation, the mainlobe and sidelobes are thesame in space. Therefore, reconnaissance aircraft cannot gain any radar infor-mation in the way that beam scanning based on the mainlobe in a traditionalradar does.

2. SIAR is able to realize long-time coherent integration, and lower transmissionpower is required for the fixed detection range compared to a conventional radar. Ifsignals with a large time-bandwidth product are employed, SIAR achieves loweraverage radiating power. Therefore, it has good invisibility and cannot be eas-ily scouted.

3. SIAR is an active array radar. Its frequency codes and phase codes from each trans-mit element are different, vary at random, and belong to complex waveforms. Thus,even though the signal is captured, it is difficult to obtain detailed parameters ofradar waveform. The position of the transmit array element and its operating fre-quency in particular cannot be obtained, so the reconnaissance receiver is unableto obtain the transmitting pattern.

4. The array elements of SIAR are very simple and distant from each other, so SIARhas a better concealment performance.

In conclusion, SIAR has good anti-reconnaissance performance.

1.3.3 Anti-ARM of SIAR

With the rapid development of ARM, it now has the fatal capability to destroy allhigh radar-like power radiation sources within 500 MHz to 20 GHz, which becomesa serious threat to the survival of the radar system. Dealing with ARMs is one of theimportant research topics that modern radars should face.

There are two main approaches anti-ARM [18]: one is the “hard” countermea-sure, namely intercepting or destroying adversary ARMs by launching missiles, whichrequires the radar system to have very high sensibility and instantly find targets likeARMs (especially stealth ARM) with a very small RCS; the other is the “soft” coun-termeasure, namely taking advantage of active decoys and radar systems to form anactive decoying system, and luring the ARMs into a safe impact area to ensure thatthe radar works as usual. For example, the AN/MPQ-53 phased array radar used inthe American Patriot air-defense system employs an active decoy.

Introduction 7

To avoid ARM attacks, the main advantages of the SIAR radar system are asfollows:

1. SIAR can instantly find the attacking ARM (including the stealth ARM). The ARMhas the resonant effect in the meter wave band, which significantly increases itsscattering cross-section (RCS). For example, for a missile with several meters, theRCS is about 0 dB m2 in the very high frequency (VHF) band [19] and less than−10 dB m2 in 1000 MHz; that is to say, the target’s RCS in the VHF band andmicrowave band differs by 10 dB due to the resonant effect. Figures 1.1 and 1.2show the results of experimental data processing by the meter wave radar duringone ARM outfield test [18], and it becomes obvious that the echoes from a missileand an airplane are commensurable. It shows that the meter wave radars have agreat advantage in finding the incoming ARM in a timely manner. SIAR has the

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Figure 1.1 Contours of range of Doppler

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Figure 1.2 Processing results of the Doppler channel of airplane and missile

8 Synthetic Impulse and Aperture Radar (SIAR)

same advantage in the meter wave band. In addition, since SIAR can implementlong-time coherent integration and the number of integration pulses can be up tohundreds, it not only has high sensibility to ARMs but also strong capability invelocity resolution when detecting ARM-like high-speed moving targets, which isbeneficial to distinguish, find, and finally intercept or destroy the ARM timely inthe spatial pace.

2. The passive seeker of ARM uses monopulse technology to track and destroy radi-ation sources, making SIAR difficult for it to track. Since SIAR works in the meterwave band and is restricted by the size of the seeker on the antenna aperture, eventhe most advanced ARM presently has difficulty in dealing with the radar workingbelow 500 MHz (except by carpet bombing).

3. SIAR can apply frequency sparse technology to insert deception signals and useactive decoy systems to avoid the ARM’s attack.

4. SIAR belongs to large array radars, and its transmitting and receiving units can bedetached. Even if a few array elements are damaged, it can work as usual with littleimpact on its performance. Furthermore, due to its simple structure and completelyidentical transmitting and receiving array elements, SIAR is very easy to repair.

As discussed above, SIAR possesses a certain warning ability, works in the meterwave band, and has potential advantages in regards to anti-ARM and anti-destruction.

1.3.4 Anti-interference of SIAR

There are many approaches to implement interference with radars, which can be cat-egorized into two main kinds: active interference and passive interference. Improvingthe resolution and factors against clutters are effective measures to counter passiveinterference; however, the real threat to radar is active interference. Active interferencehas many forms, such as spot interference, deceptive interference, and noise barrageinterference. Due to the particularity of the form of signals, noise barrage interferenceis the main issue in SIAR.

There are several advantages for anti-interference in SIAR systems:

1. Long-time coherent integration. Since SIAR adopts omnidirectional radiation,long-time coherent integration can be obtained in all directions. The number ofpulses Ni for coherent integration in SIAR is up to the thousands, much morethan that of conventional radars. For example, if Ni = 4096, the increment ofthe signal-to-interference plus noise ratio (SINR) after coherent integration is10 log(Ni)≈ 36 dB.

2. Application of signals with a large time-bandwidth product. SIAR can employsignals with large time-bandwidth product (such as phase coding signal) to improvethe signal-to-noise ratio. For example, if the time-width of a transmitting pulse isincreased by 10 times, the SINR will be increased by 10 dB.