139,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Analyzes and discusses the operating principle, signal processing method, and experimental results of this advanced radar technology This book systematically discusses the operating principle, signal processing method, target measurement technology, and experimental results of a new kind of radar called synthetic impulse and aperture radar (SIAR). The purpose is to help readers acquire an insight into the concept and principle of the SIAR, to know its operation mode, signal processing method, the difference between the traditional radar and itself, the designing ideals, and the developing method. It includes 10 chapters. Chapter 1 gives an introduction to the basic principle of SIAR and its characteristic of four antis. Chapter 2 introduces the operating principles and system constitution of SIAR. Chapter 3 presents the main waveforms and the corresponding signal processing methods. Chapter 4 is about the long-time integration technique. Chapter 5 shows the high-accuracy measurement and tracking of 4D parameters of target in SIAR. The range-angle coupling and decoupling are introduced in Chapter 6, where a criteria for transmit frequency optimization of array elements is studied to overcome the coupling among range, azimuth and elevation. In Chapter 7, detection and tracking of targets in strong interference background is investigated. Chapter 8 analyzes quantitatively the influence of array error on the tracking accuracy of SIAR. Expansion of impulse and aperture synthesis to HF band and microwave band are introduced respectively in Chapter 9 and Chapter 10. The operating principle of the novel bi-static surface wave radar system, as well as the experimental system and the experimental results are included in Chapter 9. Written by a highly experienced author with extensive knowledge of SIAR (Chen), the book can be used as a reference for engineering technical personnel and scientific research personnel working in the research of SIAR, MIMO radar, digital radar or other new type of radar. It can also be a reference for teachers and students in universities who engage in related professional work. * Details the operating principle, signal processing method, target measurement technology, and experimental results of synthetic impulse and aperture radar (SIAR) * Expands the technique of impulse and aperture synthesisfrom the VHF band to the HF band and the microwave band * Written by a leading author with many years' research and practical experience in sparse array SIAR, a typical MIMO radar Engineers, researchers and postgraduates working in radar engineering will find this an invaluable resource.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 494
Veröffentlichungsjahr: 2014
Ähnliche
Table of Contents
Title Page
Copyright
About the Authors
Preface
Acknowledgments
Chapter 1: Introduction
1.1 Development of Modern Radar
1.2 Basic Features of SIAR
1.3 Four Anti Features of SIAR
1.4 Main Types of MIMO Radar
1.5 SIAR and MIMO Radar
1.6 Organization of This Book
References
Chapter 2: Radar Common Signal Waveform and Pulse Compression
2.1 Mathematical Form and its Classification of Radar Signal
2.2 The Ambiguity Function and Radar Resolution
2.3 FM Pulse Signal and its Pulse Compression
2.4 Phase Coded Pulse Signal and its Processing
2.5 Stepped-Frequency Pulse Signal and its Processing
2.6 Orthogonal Waveform
2.7 MATLAB® Program List
References
Chapter 3: System Design of SIAR
3.1 Introduction
3.2 Principles of SIAR
3.3 Synthesis of Transmit Pulse and Aperture
3.4 4D Ambiguity Function of SIAR
3.5 Radar Equation of SIAR and its Characteristics
3.6 Experimental System of SIAR
3.7 Gain and Phase Calibration of SIAR
3.8 Experimental Results of SIAR
3.9 SIAR with Large Random Sparse Array
3.10 Brief Summary
3.11 MATLAB® Program List
References
Chapter 4: Waveform and Signal Processing of SIAR
4.1 Introduction
4.2 Waveform and Signal Processing Flow of SIAR
4.3 Application of LFM in SIAR
4.4 SIAR Performance Analysis of Pulse Compression based on Phased Codes
4.5 Pulse-to-Pulse Frequency Code Agility and its Signal Processing Flow
4.6 Group-to-Group Frequency Code Agility and its Signal Processing
4.7 Brief Summary
4.8 MATLAB® Program List
Appendix 4A Deductions of Some Equations in This Chapter
References
Chapter 5: Long-Time Coherent Integration of SIAR
5.1 Introduction
5.2 Features and Faults of Long-Time Coherent Integration of SIAR
5.3 Long-Time Coherent Integration Based on Motion Compensation and Time-Frequency Analysis
5.4 Long-Time Coherent Integration Based on Pulse Synthesis of Stepped Frequency
5.5 Computer Simulation
5.6 Brief Summary
References
Chapter 6: Digital Monopulse Tracking Technique of SIAR
6.1 Overview of the Monopulse Tracking Technique
6.2 Tracking Processing and Signal Model of SIAR
6.3 Precision Measurement of the Target Range
6.4 Measurements of the SIAR Target's Direction
6.5 Measurement of Doppler Frequency
6.6 Brief Summary
References
Chapter 7: Coupling and Decoupling between Range and Angle
7.1 Introduction
7.2 Coupling Influence of Angular Error on Range Measurement
7.3 Coupling Influence of Range Quantization Error on Angle Measurement
7.4 Range-Angle Coupling Analysis Based on the Fisher Information Matrix
7.5 Frequency Code Optimization and Three-Dimensional Decoupling Analysis
7.6 Computer Simulation
7.7 Brief Summary
References
Chapter 8: Target Detection and Tracking in SIAR under Strong Jamming
8.1 Introduction
8.2 Anti-Jamming Measures of the SIAR System
8.3 Adaptive Nulling and Computer Simulation for the Phased Array Radar
8.4 Adaptive Nulling and Computer Simulation for SIAR
8.5 Target Range Measurement in SIAR Under Active Jamming
8.6 Target Direction Measurement in SIAR Under Active Jamming
8.7 Performance Analysis of Sidelobe Cancelation in SIAR
8.8 Summary
8.9 MATLAB® Program List
References
Chapter 9: Effects of Array Error on SIAR Tracking Accuracy
9.1 Introduction
9.2 Effect of Amplitude and Phase of the Array Element on Tracking Accuracy
9.3 Influence of Channel Mismatch on Tracking Accuracy
9.4 Influence of Orthogonal Channel Imbalance on Tracking Accuracy
9.5 Summary
References
Chapter 10: Bistatic Synthetic Impulse and Aperture Ground Wave Radar Experimental System
10.1 Introduction
10.2 The Composition and Characteristics of the Test System
10.3 The Parameter Design of the Waveform of the Bistatic Synthetic Impulse and Aperture Ground Wave Radar
10.4 Working Principles of the Bistatic Synthetic Impulse and Aperture Ground Wave Radar
10.5 Sea Clutter Characteristic of the Bistatic HF Ground Wave Radar
10.6 Results of Real-Data Processing
10.7 Brief Summary
References
Chapter 11: Microwave Sparse Array Synthetic Impulse and Aperture Radar
11.1 Introduction
11.2 Transmit Signal Waveform of MSA-SIAR
11.3 The Array and its Optimization of MSA-SIAR
11.4 The Signal Pre-processing Method Based on Digital Dechirp Processing
11.5 MSA-SIAR Based on IDFT Coherent Synthesis
11.6 Spatial Domain Synthetic Bandwidth Method of MSA-SIAR
11.7 Summary
References
Bibliography
Index
This edition first published 2014
© 2014 National Defense Industry Press. All rights reserved.
Published by John Wiley & Sons Singapore Pte. Ltd., 1 Fusionopolis Walk, #07-01 Solaris South Tower, Singapore 138628, under exclusive license by National Defense Industry Press in all media and all languages throughout the world excluding Mainland China and excluding Simplified and Traditional Chinese languages.
For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com.
All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as expressly permitted by law, without either the prior written permission of the Publisher, or authorization through payment of the appropriate photocopy fee to the Copyright Clearance Center. Requests for permission should be addressed to the Publisher, John Wiley & Sons Singapore Pte. Ltd., 1 Fusionopolis Walk, #07-01 Solaris South Tower, Singapore 138628, tel: 65-66438000, fax: 65-66438008, email: [email protected].
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.
Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The Publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the Publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought.
MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This book's use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB® software.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. It is sold on the understanding that the publisher is not engaged in rendering professional services and neither the publisher nor the author shall be liable for damages arising herefrom. If professional advice or other expert assistance is required, the services of a competent professional should be sought.
Library of Congress Cataloging-in-Publication Data
Synthetic impulse and aperture radar (SIAR) : a novel multi-frequency MIMO radar /
Baixiao Chen and Jianqi Wu.\hfill}
pages cm
Includes 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 2014
621.3848′5--dc23
2013030811
ISBN: 978-1-118-60955-2
About the Authors
Baixiao Chen was born in Susong, Anhui, China, in 1966. In 1987, he graduated from Anhui University of Technology. In 1994 and 1997, he received an MS degree in circuit and system and a PhD in signal and information processing at Xidian University, China. He is currently a Professor and Academic Leader of Signal and Information Processing and Doctoral Tutor in National Laboratory of Radar Signal Processing, Xidian University. His current research interests include the synthetic impulse and aperture radar (SIAR), array signal processing, and new 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 are indexed by SCI and EI.
Jianqi Wu was born in Yibin, Sichuan, China, in 1966. In 1987 and 1990, he received a BS degree at Beijing University of Aeronautics and Astronautics and an MS degree at the University of Electronic Science and Technology respectively. He is the vice-director and director of Science and Technology Commission of CECT 38, the vice-president of Hefei Association for Science and Technology, a member of GAD scout measurement professional group, and the director of Chinese Institute of Electronics. He has been working in radar for more than 20 years. He was in charge of the key national defense advance research project “Sparse Array Synthetic Impulse and Aperture Radar Experimental System” and several key model projects. He is the author of over 10 journal articles. He has won a first class National Scientific and Technological Progress Award, two second class National Scientific and Technological Progress Awards, a first class National Defense Scientific and Technological Progress Prize, and an outstanding contribution award of Science and Technology of Hefei.
Preface
Modern wars are driving the development of stealth technology, anti-radiation missiles (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 series of 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-wave distributed radar with capability and performance of anti-stealth, low probability of interception, ARM, anti-interference, four-dimensional parameter estimate and high accuracy. The SIAR provides an effective approach to detect and track stealth aircrafts and other low-altitude targets for early warning and guidance. The SIAR has overcome the disadvantage of low resolution in the meter-wave radar by adopting a sparse separated antenna. Each transmitting antenna is omnidirectional and radiates an orthogonal frequency-coding signal, so that the entire space can be symmetrically covered. The transmitting beam and receiving beam is formed at the receiving station via signal processing. The SIAR has many differences from the conventional radar for the special system and operation mode, which rises some new problems. The SIAR is a novel multifrequency multiple-input multiple-output (MIMO) radar.
This book provides a systematic description of the working principle, signal processing procedures, target measurement techniques, and experimental results of the SIAR in compliance with engineering practice. In addition, the synthetic impulse and aperture can also be applied in the radar of the high-frequency (HF) band and the microwave band. The coast–ship bistatic HF surface wave SIAR experimental system and the microwave sparse-array SIAR have also been described.
The book contains eleven chapters and is organized as follows. Chapter 1 by Baixiao Chen and Jianqi Wu gives an introduction to the SIAR, including the basic character and the capability of anti-stealth, anti-ARM, and anti-interference. Chapter 2 by Baixiao Chen and Wei Zhu gives the common radar waveform, including the FM pulse signal, phase coded signal, stepped-frequency pulse signal, and orthogonal waveforms. The mathematical form of the radar signal, the ambiguity function, and the 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 the operating principle and system structure of the SIAR. Chapter 4 by Baixiao Chen and Jianqi Wu describes the waveforms of SIAR and the corresponding signal processing procedures. Chapters 5 to 9 are written by Baixiao Chen. In Chapter 5, long-time coherent integration techniques of the SIAR are discussed. According to the features and open questions of long-time coherent integration, two kinds of long-time coherent integration algorithm are proposed. One is based on motion compensation and time-frequency analysis; the other is based on stepped-frequency impulse synthesis. Detailed derivations of digital mono-pulse tracking, used for precision measurement of the target (including distance, azimuth, elevation, and Doppler frequency 4D parameters with the transmitting aperture and receiving aperture simultaneously), is presented in Chapter 6. Chapter 7 is dedicated to describing coupling between the range and angle in the SIAR. The influence of coupling and the method of decoupling is analyzed. In order to overcome the coupling effect among range, azimuth, and elevation, an optimized frequency-coding criterion of the transmitting signals is studied. Chapter 8 treats the detection and tracking of the target under a background of strong interference. The adaptive interference nulling techniques constitute the main topic. Also, the effects of the aperture–bandwidth product, gain-phase errors, and quantizing noise in the analog/digital (A/D) converter to a large circular-aperture SIAR are quantitatively analyzed. Chapter 9 deals with the impact on tracking accuracy of the SIAR caused by array perturbation, including gain-phase errors, channel mismatch, and unbalance among orthogonal channels. Chapter 10 by Baixiao Chen and Duofang Chen contains the bistatic surface-wave synthetic impulse and aperture radar (BSW-SIAR) experimental system. This includes the operating principle and experimental results of this over-the-horizon (OTH) radar. The microwave sparse array synthetic impulse and aperture radar is demonstrated 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 the concept 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 the State University of New Jersey and Bell Labs described it as follows: “Recently, a new and interesting concept in array radar has been introduced by the synthetic impulse and aperture radar (SIAR) …” Therefore, publication of this book should play a positive 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 signal processing procedures of the SIAR, and the differences from conventional radars. The design thoughts, development methods, and some special considerations of the SIAR are also included.
The author has been working on system design and signal processing of radar in the past 20 years with professional theories and much engineering experience. More than 80 papers about the SIAR have been published. This book is a summary of 20 years of research on the SIAR. It is hoped that this book will be a useful reference for working 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 book for the reader to better understand the SIAR and MIMO radar.
I wish to thank academicians Erke Mao, Xiaomo Wang, and Manqing Wu of the Chinese Academy of Engineering, Zhen Bao of the Chinese Academy of Sciences, Professor Yingning Peng of Tsinghua University, and Professor Shouhong Zhang of Xidian 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 Yingning Peng 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 the development 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 and all editors.
Acknowledgments
I am grateful to Xidian University and National Laboratory of Radar Signal Processing for supplying me with such a perfect working condition and good academic circumstances. I should give my thanks to the No. 38 Research Institute of China Electronics Technology Group Corporation (CETC) for helping us to accomplish the project.
I would like to extend my sincere thanks to Professor Li Jian for many valuable comments.
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 discussion and enormous help.
My thanks also go to my students Zhu Wei, Zheng Guimei, Wang Yi, Gao Longchao, Lu Jiazhan, Wang Yu, Chen Genhua, Guo Weina, Zheng Qiaozhen, and Xu yebin, who did some of the translation work and revised most of the figures in this book. I am also thankful for the help from Chen Duofang, Yang Minglei, and Qin 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 to make this book possible. My deepest gratitude goes to my family; without their care and support, this book would have been nearly impossible. Most of all, I am thankful to my wife, Xu Hui, for her love and support, and my son, Chen Runkang, for his sweet smiles.
Chen BaixiaoJuly 5, 2013
Chapter 1
Introduction
1.1 Development of Modern Radar
With the development of microelectronics, very large scale integrated converters (VLSICs), new materials, and advanced productive technologies, modern radar techniques have progressed dramatically. Major development trends in the modern radar are given as follows:
With the development of stealth techniques, anti-radiation missiles (ARMs), electronic countermeasures (ECMs), and low-altitude penetration [1–6], new challenges and higher demands are expected. As traditional radars are incapable of dealing with these 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 has been 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 materials to reduce radar cross-section (RCS). These techniques are widely acknowledged as useful measures for centimeter wave radars. However, it has little impact for electromagnetic waves of longer wavelengths (such as meter waves). Since the RCS of a target is related to the radar wavelength with the form RCS = nλ [7], where n depends on the geometrical shape of the target and has a value between 0 and 2, and λ is the wavelength. At the international conference on radar systems in 1985, Moraitis analyzed the influence of radar frequency on the detection of stealth targets. The results show that the RCS of stealth aircraft is higher at the metric band than at the S-band by 15–30 dB. Meanwhile, the impedance loading cannot be carried out since the metric band is the resonance region of the airframe. Absorbing material coatings are influenced by frequency characteristics. Currently, the effective frequency is between 1 and 20 GHz, with the coating thickness lying between 1/10 and 1/4 wavelength. For the metric wave, it is impossible for the coating thickness to be up to an order of 10 cm. Therefore, the absorbing material coating is not a threat to the metric radar. The absorbing penetrating materials also cannot be applied effectively in the metric wave due to the frequency characteristics of the materials. Thus, the metric wave radar has a good capability in detecting stealth targets.
However, traditional metric radars have difficulties in meeting the requirements of modern warfare due to their wide beams, poor positioning accuracy, and especially their inability to track and guide multiple targets. In recent years, radar researchers are trying to improve the performance of resolution, low-altitude detection, anti-jamming, multiple target detection with the metric radars. However, these efforts are only improvements to the traditional radar system, so it is difficult to meet their 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 and tracking) radar system [8–15] To overcome the inherent weakness of low angular resolution, the large sparse array is employed in this metric wave radar. Due to its new transmitting signal system and advanced signal processing techniques, the isotropic illumination for the whole space can be performed with a large antenna array, which has strong directivity. Aperture synthesis and impulse synthesis for signals with large time widths are performed at the same time, so an LPI can be realized.
1.2 Basic Features of SIAR
The basic concepts of SIAR can be summarized as follows:
SIAR uses multiple antennas to transmit orthogonal signals with multicarrier frequencies. These signals have unique characteristics in wavelength selection, antenna types, Doppler processing, and beamforming [16]:
The most significant technical feature of SIAR is that it can realize nondirectional emission and form multiple “stacked” beams simultaneously. Therefore, the long-time coherent integration can be achieved simultaneously at all beam directions so as to 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 missiles, stealth targets, and reentry InterContinental ballistic missile (ICBM) warheads. Improving the radar detection ability has always been a hot topic, and it becomes especially important with the advancement of stealth techniques. To improve detection ability, it is not enough to increase the transmitted power. This new-style radar principle, waveform design, and signal processing are also needed.
The general radar usually uses coherent integration techniques or noncoherent integration techniques to improve detection ability, but the number of pulses available for integration 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 repetition 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 is much lower. In order to suppress the clutter, sometimes only part of the pulses can be integrated so the signal-to-noise ratio (SNR) improvement gained through integration is limited.
Since transmit and receive beamformings are realized through signal processing at the receiving end, impulse synthesis in SIAR can keep the beam at certain directions (even one direction). Therefore, multiple beams or stacked beams (including transmitting beams and receiving beams) can be simultaneously achieved at the receiving end. These beams can even cover the entire spatial space without beam scanning and always track targets. This is equivalent to the “burn-through” operational mode in conventional radar, though the conventional radar only operates in one direction in the “burn-through” mode. Since there is no beam scanning in SIAR, the integration time is only determined by the target's velocity and the radar parameters, independent of the beam scanning time on the target. Therefore, SIAR can obtain a larger number 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 transmitted signals [16, 17], improving the detection range and resolution capability of the radar.
SIAR has two advantages in anti-stealth as follows:
1.3.2 Anti-reconnaissance of SIAR
Before implementing synthetic electronic jamming or transmitting ARM to the radar system, it is important to confirm the working state of the radar according to its radiation information to implement effective jamming or attack. In order to avoid jamming and attacking, modern radar must have high anti-reconnaissance performance. In this respect, SIAR is mainly characterized by Chen [16]:
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 all high radar-like power radiation sources within 500 MHz to 20 GHz, which becomes a serious threat to the survival of the radar system. Dealing with ARMs is one of the important research topics that modern radars should face.
There are two main approaches anti-ARM [18]: one is the “hard” countermeasure, namely intercepting or destroying adversary ARMs by launching missiles, which requires the radar system to have very high sensibility and instantly find targets like ARMs (especially stealth ARM) with a very small RCS; the other is the “soft” countermeasure, namely taking advantage of active decoys and radar systems to form an active decoying system, and luring the ARMs into a safe impact area to ensure that the radar works as usual. For example, the AN/MPQ-53 phased array radar used in the American Patriot air-defense system employs an active decoy.
To avoid ARM attacks, the main advantages of the SIAR radar system are as follows:
Figure 1.1 Contours of range of Doppler
Figure 1.2 Processing results of the Doppler channel of airplane and missile
As discussed above, SIAR possesses a certain warning ability, works in the meter wave 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 categorized into two main kinds: active interference and passive interference. Improving the resolution and factors against clutters are effective measures to counter passive interference; however, the real threat to radar is active interference. Active interference has many forms, such as spot interference, deceptive interference, and noise barrage interference. Due to the particularity of the form of signals, noise barrage interference is the main issue in SIAR.
There are several advantages for anti-interference in SIAR systems:
To sum up, SIAR can take full advantage of methods in time domain, frequency domain, and space domain to cancel out interference. Therefore, compared with conventional radars, it has more methods to anti-interference, namely a stronger anti-interference ability. A more detailed discussion will be given in Chapter 7.
1.4 Main Types of MIMO Radar
The concept of the MIMO (multiple-input multiple-output) radar originates from MIMO communications. The advantages achieved by MIMO communication have led to its application in the field of radar. Actually, RIAS invented by ONERA [3] and the sparse array SIAR developed by Chinese researchers were typical kinds of MIMO radar even before the concept of MIMO radar was put forward (this has been mentioned in references [20] and [21]). MIMO radar is mainly adopted from the idea of SIAR. They both transmit orthogonal signals by using multiple transmit antennas and receive echoes via multiple receive antennas. The transmitting directional pattern can be formed in the receiving end via signal processing. There are similarities and differences between the MIMO radar and the conventional phased array radar.
By using multiple transmit antennas to emit different kinds of signals, MIMO radar can achieve more advantages over conventional phased array radars. For example, after the transmit signals are separated at the receiving end, MIMO radar can synthesize a two-way antenna pattern and form monopulse tracking beams using both the transmitting array aperture and the receiving array aperture. This aspect is similar to SIAR, but the phased array radars cannot do it. The conventional phased array radars can be considered as SIMO (single-input multiple-output) radars, which form a one-way antenna pattern and tracking beam by using only the receiving array aperture, as does also the signal processing, which is for the receiving array only. For now, MIMO radar can be classified in many different ways. According to the distribution of the antennas, MIMO radars can be classified as the centralized MIMO radar and the distributed MIMO radar. Based on the method of coherent signal processing, a MIMO radar can be classified as the coherent MIMO radar and the noncoherent MIMO radar. The centralized MIMO radar usually adopts coherent processing and the distributed MIMO radar utilizes noncoherent processing because its antennas are dispersive in the position and the received signals from each channel are not coherent. According to the waveform of the transmitting signal, a MIMO radar can be classified as the multicarrier orthogonal waveform MIMO radar, the phase coding orthogonal waveform MIMO radar, and the nonorthogonal waveform MIMO radar. Distributed MIMO radars emphasize detection from different azimuths. Large objects such as an aircraft presents a smaller RCS viewed from the front and a larger RCS viewed from the side or back. The RCS of a stealth aircraft viewed from certain directions will be dozens of decibels more than that from the front direction. Figure 1.3 is the frequency-azimuth distribution of RCS measured at HH polarization (horizontal polarization transmitting and horizontal polarizing receiving) on the reduced-scale model of a certain target (B-2). As seen from the figure, the RCS viewed from the front is 10 dB lower than that from the normal direction of the wing. One major advantage of the centralized MIMO radar is that the transmit array aperture can be utilized to improve the degree of freedom and the related performance in received signal processing. If not emphasized already, all MIMO radars mentioned in this book refer to the centralized coherent MIMO radar.
Figure 1.3 Frequency-azimuth distribution of RCS
1.5 SIAR and MIMO Radar
General array signal processing, such as direction of arrival (DOA) estimation and super-resolution, only has a one-way reception and the array is only relative to the receive array of the MIMO radar. A coherent MIMO radar uses multiple antennas to transmit signals simultaneously. After the radiation, signal components of the transmitting antenna are separated from each received signal at the receiving end, and the transmitting array aperture and the receiving array aperture are utilized simultaneously while array signal processing is carried out. This kind of two-way array signal processing is quite different from the traditional one-way array signal processing. The preliminary studies of two-way array signal processing are presented in the article.
Multiple transmitting and multiple receiving antennas are used in an MIMO radar so the degree of freedom can be greatly increased [22, 23]. For example, the maximum degree of freedom of a system with M transmitting elements and N receiving elements is (M · N − 1). A centralized MIMO radar with multiple transmitting antennas has a smaller array aperture compared to the netted radar. An MIMO radar puts more emphasis on the coherent processing of the transmitting signal while the netted radar focuses more on the plot fusion and coverage of the space with multiple radars to improve the target detection performance.
An MIMO radar also uses multiple antennas to transmit quadrature signals simultaneously to ensure energy coverage of the entire surveillance space. Therefore, the basic features of the MIMO radar are similar to the SIAR. If the MIMO radar works simultaneously with multicarrier frequencies, then its processing method is also similar to the SIAR. The common features of a coherent MIMO radar and an SIAR are given as follows:
The major differences between the general MIMO radar and SIAR can be summarized as follows [24]:
Hence, SIAR is a kind of orthogonal waveform MIMO radar with a multicarrier.
1.6 Organization of This Book
It is because SIAR uses multiple antennas to transmit mutually orthogonal signals with multiple carrier frequencies that it is very different from the conventional radar systems in many aspects, such as operating principle, system configuration, signal processing method, and target parameters measure. Therefore, this book gives a systemic introduction of the system principle and techniques of this kind of radar. This book includes 11 chapters. Chapters 1 to 9 address the techniques of impulse and aperture synthesis with the experimental SIAR system in detail. The main content includes:
Combined with the functional requirements of radar, Chapters 10 and 11 introduce the popularization and applications of synthetic impulse and aperture technology, which are very different from the SIAR in signal forms and processing methods, thus enriching the connotation of SIAR technology. Table 1.1 compares the operating modes of the experimental system of meter wave SIAR, the experimental system of synthetic impulse and aperture ground wave radar, and the microwave sparse array SIAR.
Table 1.1 Comparison of three SIAR experimental systems
References
1. Li, N. (1987) Radar ECCM's new area: anti-stealth and anti-ARM. Acta Electronica Sinica, 15 (2), 98–104 (Published in Chinese).
2. Huang, P. (1984) An overview of aircraft stealth techniques. Systems Engineering and Electronics, 6 (1), 3–10 (Published in Chinese).
3. Farina, A. and Galati, G. (1985) An overview of current and advanced processing techniques for surveillance radar. IEEE Radar-85, pp. 175–183.
4. Liu, Z. and Ke, Y. (1992) On radar anti-stealth techniques and its problems. Modern Radar, 14 (3), 4–12 (Published in Chinese).
5. Mao, S., Lin, P., and Li, S. (1993) Some methods for weak terribly target detection. Proceedings of Anti-Stealth Techniques Workshop, Beijing, Vol. 10, pp. 64–70 (Published in Chinese).
6. Huang, W. (1993) All-around discussion for anti-stealth-aircraft techniques with informative radar. Proceedings of Anti-stealth Techniques Workshop, Beijing, People's Republic of China, Vol. 10, pp. 1–30 (Published in Chinese).
7. Moraitis, D. and Alland, S. (1985) Effect of radar frequency on the detection of shaped (low RCS) targets. IEEE Radar-85, pp. 159–162.
8. Bao, Z. and Zhang, Q. (1995) A new styles metric wave radar: synthetic impulse and aperture radar. Modern Radar, 17 (1), 1–13 (Published in Chinese).
9. Dorey, J., Blanchard, Y., and Christophe, F. (1984) Le project ‘RIAS’: une approche nouvelle du radar des surveillance aerienne. Colloque International sur le Radar, Paris, France, April 1984, pp. 505–510.
10. Dorey, J., Garnier, G., and Auvray, G. (1989) RIAS, radar à impulsion et antenna synthetique. Colloque International sur le Radar, Paris, France, April 1989, pp. 556–562.
11. Chassain, T. (1989) Calculateur de veille TMPS reel pour radar à impulsion et antenna synthetique. Colloque International sur le Radar, Paris, France, April 1989, pp. 364–369.
12. Thibaud, D. and Eglizeaud, J.P. (1989) Calculateur de poursuite 4D pour le radar à impulsion et antenna synthetique (RIAS). Colloque International sur le Radar, Paris, France, April 1989, pp. 370–374.
13. Lesturgie, M. and Thibaud, D. (1989) Fouillis de mer et limitations introduities dans le domaine de la detectabilite des cibles en VHF. Colloque International sur le Radar, Paris, France, April 1989, pp. 132–137.
14. Lesturgie, M. and Renoux, E. (1989) Etude des anomalise de propagation à sita bas et consequences sur les grands reseaux phases. Colloque International sur le Radar, Paris, April 1989, pp. 152–157.
15. Luse, A.S., Monina, H., Muller, D., et al. (1992) Experimental results on RIAS digital beamforming radar. International Conference on Radar, London, UK, pp. 505–510.
16. Chen, B. (1997) Researches on 4D tracking and long-time coherent integration for synthetic impulse and aperture radar. PhD thesis, Xidian University (Published in Chinese).
17. Chen, B., Zhang, S., and Wang, Y. (2001) Analysis and experimental results on sparse-array synthetic impulse and aperture radar. CIE International Conference on Radar, Beijing, People's Republic of China, pp. 76–80.
18. Chen, B., Wu, T., Zhang, S., et al. (2003) Detection of high-speed anti-radiation missiles. Journal of Xidian University, 30 (6), 726–729 (Published in Chinese).
19. Kuschel, H. (2002) VHF/UHF radar, part 1: characteristics. Electronics and Communication Engineering Journal, 14 (2), 61–72.
20. Khan, H.A., Malik, W.Q., Edwards, D.J., et al. (2005) Ultra wideband multiple-input multiple-output radar. IEEE International Conference on Radar, pp. 900–904.
21. Fishler, E., Haimovich, A., Blum, R.S., et al. (2006) Spatial diversity in radars—models and detection performance. IEEE Transactions on Signal Processing, 54 (3), 823–838.
22. Bliss, D.W. and Forsythe, K.W. (2003) Multiple-input multiple-output (MIMO) radar: degrees of freedom and resolution. Proceedings of 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA.
23. Chen, D., Chen, B. and Qin, G. (2008) Angle estimation using ESPRIT in MIMO radar. Electronics Letters, 44 (12), 770–771.
24. Chen, D., Chen, B., and Zhang, S. (2006) Multiple-input multiple-output radar and sparse array synthetic impulse and aperture radar. CIE International Conference on Radar, Shanghai, People's Republic of China, pp. 28–31.
Chapter 2
Radar Common Signal Waveform and Pulse Compression
Different from signals transmitted by communication systems, radar transmitting signals are only carriers of information that do not contain any information about the target, and all the target information is contained in an echo, which is formed by transmitting the signal's reflection (scatter). Radar transmitting signal waveforms not only determine signal processing methods but also directly affect the main performance, such as system resolution, measurement accuracy, and clutter suppress (anti-interference) ability. Therefore, signal waveform design has become an important aspect of modern radar system design [1].
The radar signal's mathematical form and its classification are first given in this chapter. Then the concept of ambiguity function and radar resolution theory are introduced, emphasizing the analysis of common radar signal waveforms and their signal processing methods, such as the frequency modulation (FM) pulse signal, phase coded signal, stepped-frequency pulse signal. Then orthogonal waveforms are introduced. Finally, MATLAB® program codes of chief illustrations in this chapter are given.
2.1 Mathematical Form and its Classification of Radar Signal
2.1.1 Signal Mathematical Form
Radar transmitting signals are generally certain signals whose parameters are known to expect an initial phase (transmitting signals of a coherent radar must keep a precise phase relationship with certain reference signals) and an echo signal, which is a random signal overlying noise and interference.
A signal can be expressed by a real function s(t), which is called a real signal, and its characteristic is finite energy or finite power. A signal with finite energy is called an energy signal; a signal with infinite energy but finite power is called a power signal. An energy spectrum density (ESD) function (the amplitude spectrum |S(ω)| is usually used in practical applications) is usually used to characterize a spectrum feature of the energy signal; as for a power signal, the power spectrum density (PSD) function is used for characterization.
Let the signal be s(t), for the energy signal, where the ESD function is defined as
2.1
For a power signal, the PSD function is defined as
2.2
where is the autocorrelation of signal s(t).
According to the signal frequency composition, a signal can be divided into a low-pass signal and a band-pass signal. The common radar signal, whose bandwidth is far less than the carrier frequency, is called a narrow pass-band signal.
A real pass-band signal can be expressed as
2.3
where is the signal amplitude modulation or envelope, is the phase modulation item, and is the carrier frequency. Compared with the phase modulation and carrier frequency, the variation of the signal envelope is a slow variation process. For low-resolution radars, envelopes of the target echo of multiple pulses that are transmitted during one beam direction are usually considered unchangeable.
The frequency modulation function of signal and instantaneous frequency are respectively
2.4
2.5
A real signal has a symmetric bilateral frequency spectrum. For a narrowband signal, since its bandwidth is far less than the carrier frequency, a double-sideband (DSB) frequency spectrum does not overlap, then only one sideband frequency spectrum is enough to completely determine the signal waveform. To simplify the analysis of the signal and system, a complex signal with single sideband (SSB) spectrum is usually adopted.
A common complex signal expression, namely the complex expression of a real signal has two types: the Hilbert transform expression method and the exponent expression method. For a narrowband signal, the two expression methods are approximately the same.
2.1.1.1 Hilbert Transform Expression Method
In general, a complex signal can be expressed as
2.6
If a complex signal is required to have unilateral frequency, then restrictions must be made on the imaginary part.
If a real signal (where X(f) is the Fourier transform of x(t)), define the complex analytic signal as
2.7
where U(f) is the step function in the frequency domain. From the property of the Fourier transform, we can obtain
2.8
where is the Hilbert transform equation of .
Thus, the frequency spectrum of a complex signal formed by Equation (2.8) can meet the demands of Equation (2.7), namely, making the negative frequency component of the original real signal counteract, and the positive component doubles. The energy of the real signal and the energy of the complex analytic signal are respectively
2.9
2.10
2.1.1.2 Exponent Expression Method
A complex analytic signal is an effective expression method used in deriving a signal's ordinary feature, but is not convenient when analyzing a concrete signal; thus, a complex signal with exponential form is often employed to substitute a complex analytic signal.
A real signal can be expressed by the real part of a complex signal with exponential form as
2.11
where is the complex exponential form of a real signal and is the complex envelope of a complex signal.
The relationship among a narrowband real signal, complex signal, and complex envelope is summarized in Table 2.1.
Table 2.1 The relationship among a narrowband real signal, complex signal, and complex envelope
The energy relationship among a narrowband real signal, complex signal, and complex envelope is
2.12
where , ,
For convenience of analysis, the signal energy is usually normalized as
2.13
The frequency spectrum of a narrowband real signal x(t) is |X(f)|, and the relationship between the frequency spectrum |Sa(f)| of its corresponding complex analytic signal and complex envelope frequency spectrum |U(f)| is shown in Figure 2.1.
Figure 2.1 Relationship among narrowband real signal, complex analytic signal, and complex envelope spectrum
For a narrowband radar signal, its complex envelope u(t) or corresponding frequency spectrum U(f) can be used for characterization completely. However, a proper waveform parameter sometimes represents certain signal features, and usually a normalized second order moment is employed as effective measurement to signal time width and bandwidth, and defining effective time width (also called effective persistence time or root of mean square time width), and effective bandwidth (also called root of mean square bandwidth) respectively as
2.14
2.15
