Systems. Advanced Radar. Waveform Design and Diversity for. Fulvio Gini, Antonio De Maio and Lee Patton. Edited by

Transcription

1 Waveform Design and Diversity for Advanced Radar Systems Edited by Fulvio Gini, Antonio De Maio and Lee Patton The Institution of Engineering and Technology

2 Contents Waveform diversity: a way forward to the future of the radar xiii 1 Classical radar waveform design Introduction Narrow-band signal Matched filter and ambiguity function Linear frequency modulated pulse Phase-coded pulse Binary sequences Polyphase sequences Coherent pulse train Mismatched filters Spectral efficiency Coherent train of diverse pulses Complementary pulses Stepped-frequency pulses Frequency-coded waveforms Multicarrier waveforms Continuous periodic waveforms Conclusions 34 References 34 2 Information theory and radar waveform design Introduction Information theory and radar waveform design Mutual information Mutual information and the Noisy Channel Coding Theorem Mutual information and radar measurement Target impulse response Maximum mutual information waveforms Maximal mutual information waveform design Recent work applying information theory to radar Summary and conclusions 59 References 60

3 vi Waveform design and diversity for advanced radar systems 3 Multistage ambiguity function and sensor placement strategies Introduction Problem formulation Multistatic ambiguity function Sensor placement in multistatic radar systems Conclusions 86 References 87 4 MIMO radar waveform design Introduction MIMO radar data model and transmission schemes FT-CDMA MIMO CAN waveforms ZCZ waveforms FDMA TDMA DDMA ST-CDMA Conclusions 116 References Passive bistatic radar waveforms Introduction The radar equation in bistatic radar The ambiguity function in bistatic radar Passive bistatic radar waveforms FM radio Analogue television Digital radio and TV Cell phone networks WiFi and WiMAX transmissions Other transmissions Summary of transmitters Examples of passive bistatic radar systems The signal and interference environment in PBR PBR processing techniques Examples of results Digital transmissions Conclusions 144 References Biologically inspired waveform diversity Introduction Waveform types Waveform diversity and the 'feeding buzz' 155

4 Contents vii 6.4 Frequency modulations Linear frequency modulation Hyperbolic frequency modulation Doppler tolerance and wideband ambiguity function Diversity processing Conclusions 169 References Continuous waveforms for automotive radar systems Introduction Waveform design Monofrequency continuous wave radar system Modulation scheme Signal processing System design Discussion Linear frequency modulated continuous waveform Modulation scheme Signal processing System design Discussion Frequency shift keying waveform Modulation scheme Signal processing System design Discussion Multiple frequency shift keying waveform Modulations scheme Signal processing System design Discussion Frequency modulation with rapid chirps Modulations scheme Signal processing System design Discussion Azimuth angle measurement Measurement of lateral velocity Radar measurement oflateral velocity Conclusion 204 References Multistatic and waveform-diverse radar pulse compression Introduction Multistatic received signal model 209

5 viii Waveform design and diversity for advanced radar systems 8.3 Multistatic adaptive pulse compression MAPC-CLEAN hybridization Bistatic projection CLEAN Hybrid CLEAN Single-pulse range-doppler imaging Stepped-frequency radar Conclusions 227 References Optimal channel selection in a multistatic radar system Introduction Bistatic geometry Monostatic and bistatic ambiguity function Monostatic and bistatic Cramer-Rao lower bounds Ambiguity function and Cramer-Rao lower bounds for a burst oflfm pulses Optimal selection of the TX-RX pair Conclusions 252 Appendix: Relation between CRLB and AF 253 References Waveform design for non-cooperative radar networks Introduction System model Problem formulation Signal-to-noise ratio Mutual interference constraints Energy constraint Code design Equivalent problem formulations Relaxation and randomization Approximation bound Performance analysis Maximization of the SNR Control ofthe induced interference Computational complexity Conclusions 278 Appendix: Solvability of the optimization problem 279 References Waveform design based on phase conjugation and time reversal Introduction Phase conjugation and time reversal theoretical background Time reversal invariance in wave propagation 284

6 Contents ix 11.3 Phase conjugation and operational RADAR application Phase conjugation versus classical strategies Pencil beams (emission and reception with pencil beams) Digital beam forming (emission with wide beam, reception with DBF) Phase conjugation (emission with PC, reception with DBF) Phase conjugation and DORT methods for RADAR SNR derivation single-target case DORT eigenvalues SNR derivation multiple targets case DORT eigenvalues SNR derivation - moving target Detection criterion Phase conjugation implementation in RADAR LSEET prototype description UWB phase conjugation experiment Details ofmeasurement Results and discussion UWB DORT experiment Details of measurements Results and discussion Conclusion 311 References Space-time diversity for active antenna systems Introduction From focused beam and wide beam to multiple transmissions Space-time coding Principles Fast scanning or intra-pulse scanning Circulating pulse Circulating codes: general principle Code optimization Interleaved scanning (slow-time space-time coding) Target coherence and diversity gains Target coherence Diversity gain Coding strategy Conclusion 339 References 340

7 x Waveform design and diversity for advanced radar systems 13 Autocorrelation constraints in radar waveform optimization for detection Introduction Overview Notation Background Waveform-optimized performance Detecting a known signal Signal-filter optimization Waveform-only optimization Waveform-optimized performance Unknown targets in noise Signal model Problem formulation Waveform spectra Choosing a formulation Examples Overview Dissimilar interference Similar interference Summary 365 Appendix: Gradients and Jacobians 366 References Adaptive waveform design for radar target classification Introduction Waveform design metrics Waveform design for optimized mutual information Waveform design for optimized SNR Waveform design examples and behaviour Waveform examples Saturation behaviour Enforcing constant modulus Autocorrelation and range sidelobes Application to radar target classification Modifications for finite-duration targets Spectral variance expression for target ensembles Performance examples 404 References Adaptive waveform design for tracking Introduction to waveform-agile tracking Target tracking formulation Waveform-agile tracking 418

8 Contents xi 15.4 Waveform-agile tracking using MIMO radar Signal model for widely separated MIMO radar CRLB for MIMO widely separated radar and transmission waveform Waveform-agile MIMO radar tracking Simulation results Waveform-agile tracking in urban terrain Multipath propagation geometry Target tracking in urban terrain Adaptive waveform selection in urban tracking Simulation results Waveform-agile tracking in high clutter urban terrain Tracking in high clutter urban terrain Adaptive waveform selection Simulation results Waveform-agile tracking in urban terrain using MIMO radar MIMO radar signal model and tracking in urban terrain Adaptive waveform selection Simulations results Conclusions 445 References Adaptive polarization design for target detection and tracking Introduction Target detection in heavy inhomogeneous clutter Polarimetric radar model Detection test Target detection optimization Polarimetric MIMO radar with distributed antennas for target detection Signal model Problem formulation Detector Scalar measurement model Numerical results Adaptive polarized waveform design for target tracking based on sequential Bayesian inference Sequential Bayesian framework for adaptive waveform design Target dynamic state model and measurement model Target tracking using sequential Monte Carlo methods Optimal waveform design based on posterior Cram6r-Rao bounds Numerical examples 489

9 xii Waveform design and diversityfor advanced radar systems 16.5 Conclusions 492 References Knowledge-aided transmit signal and receive filter design in signal-dependent clutter Introduction System model Problem formulation and design issues Receive filter optimization: solution to problem P'"' Radar code optimization: solution to problem V[n) Transmit-receive system design procedure Performance analysis Uniform clutter environment Heterogeneous clutter environment Conclusions 523 Appendix A: Proof of Lemma Appendix B: Proof of (17.31) 525 Appendix C: Proof of Proposition Appendix D: Mutual information analysis 527 Appendix E: Proof of Proposition Appendix F: Proof oflemma Appendix G: Proof of Lemma References 531 Notation 535 Index 537