MIMO radar signal processing
Multiple-Input Multiple-Output (MIMO) radar has been receiving increasing attention from researchers, practitioners, and funding agencies. This is the first book to present a comprehensive and coherent picture of this emerging field, which is likely to become the standard reference in the field. The...
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Group Author: | ; |
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Published: |
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Literature type: | Electronic eBook |
Language: | English |
Subjects: | |
Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/9780470391488 |
Summary: |
Multiple-Input Multiple-Output (MIMO) radar has been receiving increasing attention from researchers, practitioners, and funding agencies. This is the first book to present a comprehensive and coherent picture of this emerging field, which is likely to become the standard reference in the field. The book introduces recent developments in MIMO radar in a tutorial manner to stimulate new concepts, theories, and applications on the topic, as well as to foster further cross-fertilization of ideas with MIMO communications. It is valuable for radar system designers, research groups, and graduate stu. |
Carrier Form: | 1 online resource (xviii, 448 pages) : illustrations |
Bibliography: | Includes bibliographical references and index. |
ISBN: |
9780470391488 0470391480 9780470391433 047039143X |
Index Number: | TK6575 |
CLC: | TN95 |
Contents: | COVER -- CONTENTS -- PREFACE -- CONTRIBUTORS -- 1 MIMO Radar -- Diversity Means Superiority -- 1.1 Introduction -- 1.2 Problem Formulation -- 1.3 Parameter Identifiability -- 1.3.1 Preliminary Analysis -- 1.3.2 Sufficient and Necessary Conditions -- 1.3.3 Numerical Examples -- 1.4 Nonparametric Adaptive Techniques for Parameter Estimation -- 1.4.1 Absence of Array Calibration Errors -- 1.4.2 Presence of Array Calibration Errors -- 1.4.3 Numerical Examples -- 1.5 Parametric Techniques for Parameter Estimation -- 1.5.1 ML and BIC -- 1.5.2 Numerical Examples -- 1.6 Transmit Beampattern Designs -- 1.6.1 Beampattern Matching Design -- 1.6.2 Minimum Sidelobe Beampattern Design -- 1.6.3 Phased-Array Beampattern Design -- 1.6.4 Numerical Examples -- 1.6.5 Application to Ultrasound Hyperthermia Treatment of Breast Cancer -- 1.7 Conclusions -- Appendix IA Generalized Likelihood Ratio Test -- Appendix 1B Lemma and Proof -- Acknowledgments -- References -- 2 MIMO Radar: Concepts, Performance Enhancements, and Applications -- 2.1 Introduction -- 2.1.1 A Short History of Radar -- 2.1.2 Definition and Characteristics of MIMO Radar -- 2.1.3 Uses of MIMO Radar -- 2.1.4 The Current State of MIMO Radar Research -- 2.1.5 Chapter Outline -- 2.2 Notation -- 2.3 MIMO Radar Virtual Aperture -- 2.3.1 MIMO Channel -- 2.3.2 MIMO Virtual Array: Resolution and Sidelobes -- 2.4 MIMO Radar in Clutter-Free Environments -- 2.4.1 Limitations of Cramér-Rao Estimation Bounds -- 2.4.2 Signal Model -- 2.4.3 Fisher Information Matrix -- 2.4.4 Waveform Correlation Optimization -- 2.4.5 Examples -- 2.5 Optimality of MIMO Radar for Detection -- 2.5.1 Detection -- 2.5.2 High SNR -- 2.5.3 Weak-Signal Regime -- 2.5.4 Optimal Beamforming without Search -- 2.5.5 Nonfading Targets -- 2.5.6 Some Additional Benefits of MIMO Radar -- 2.6 MIMO Radar with Moving Targets in Clutter: GMTI Radars -- 2.6.1 Signal Model -- 2.6.2 Localization and Adapted SNR -- 2.6.3 Inner Products and Beamwidths -- 2.6.4 SNR Loss -- 2.6.5 SNR Loss and Waveform Optimization -- 2.6.6 Area Search Rates -- 2.6.7 Some Examples -- 2.7 Summary -- Appendix 2A A Localization Principle -- Appendix 2B Bounds on R(N) -- Appendix 2C An Operator Norm Inequality -- Appendix 2D Negligible Terms -- Appendix 2E Bound on Eigenvalues -- Appendix 2F Some Inner Products -- Appendix 2G An Invariant Inner Product -- Appendix 2H Krönecker and Tensor Products -- 2H.1 Lexicographical Ordering -- 2H.2 Tensor and Krönecker Products -- 2H.3 Properties -- Acknowledgments -- References -- 3 Generalized MIMO Radar Ambiguity Functions -- 3.1 Introduction -- 3.2 Background -- 3.3 MIMO Signal Model -- 3.4 MIMO Parametric Channel Model -- 3.4.1 Transmit Signal Model -- 3.4.2 Channel and Target Models -- 3.4.3 Received Signal Parametric Model -- 3.5 MIMO Ambiguity Function -- 3.5.1 MIMO Ambiguity Function Composition -- 3.5.2 Cross-Correlation Function under Model Simplifications -- 3.5.3 Autocorrelation Function and Transmit Beampatterns -- 3.6 Results and Examples -- 3.6.1 Orthogonal Signals -- 3.6.2 Coherent Signals -- 3.7 Conclusion -- References -- 4 Performance Bounds and Techniques for Target Localization Using MIMO Radars -- 4.1 Introduction --T$1. |