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图书分类 > 物理 > 声学 > 自适应雷达信号检测与距离估计（英文版）
本书系统介绍了雷达信号检测领域的发展前沿和最新研究成果，重点阐述了知识基自适应检测和泄露自适应检测两方面内容。对于知识基自适应检测，包括阵列斜对称检测、杂波谱对称检测和贝叶斯检测三部分内容，实现了对各种先验知识的有效利用，大幅提高雷达在非均匀环境下的探测性能。对于泄露自适应检测，在完成离散时间信号建模基础上，构建了相应的二元假设检验问题，采用广义似然比等检验准则给出解决方案，将以泄露目标能量创新地加以利用，不仅有效减小泄露损失，还实现了对目标距离的有效估计。进一步探讨了提高泄露检测性能的措施，包括对时间序列进行过采样、利用前述各类先验知识等。此外，本书还采用雷达实测数据对所介绍方法的有效性进行了充分验证。
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目录
- Contents
1 Introduction to Radar Systems 1
1.1 Historical Background 1
1.2 Pulsed Radar Architectures 4
1.3 An Introduction to Design Parameters 8
1.3.1 The Ambiguity Function 10
1.3.2 Doppler Resolution and the Pulse Burst Waveform 14
1.3.3 Radar Equation 19
1.4 Organization and Outline of the Book 20
References 21
2 Adaptive Radar Detection: Classical Approach 23
2.1 Analytical Models for Target and Interference 24
2.2 Decision Theory in Radar 30
2.2.1 Hypothesis Testing Problems 30
2.2.2 Design Criteria 34
2.3 Conventional Detectors for Point-Like Targets 38
2.3.1 Decision Rules 38
2.3.2 CFAR Property 42
References 43
3 Knowledge-Aided Detectors 45
3.1 Persymmetric Detectors 46
3.1.1 Problem Formulation 46
3.1.2 Detector Designs 48
3.1.3 Illustrative Examples 61
3.2 Symmetric Spectrum Detectors 72
3.2.1 Problem Formulation 73
3.2.2 Detector Designs 75
3.2.3 Illustrative Examples 84
3.3 Joint Exploitation of Persymmetry and Symmetry 90
3.3.1 Problem Formulation 90
3.3.2 Detector Designs 93
3.3.3 Illustrative Examples 96
References 100
4 Detectors with Enhanced Range Estimation Capabilities 103
4.1 Localization Detectors for Point-Like Targets 104
4.1.1 Problem Formulation 104
4.1.2 Detector Designs 106
4.1.3 Illustrative Examples 113
4.2 Polarimetric Localization Detectors 120
4.2.1 Problem Formulation 121
4.2.2 Detector Designs 122
4.2.3 Illustrative Examples 127
4.3 Oversampling Localization Detectors 134
4.3.1 Problem Formulation 135
4.3.2 Detector Designs 139
4.3.3 Illustrative Examples 146
References 152
5 Knowledge-Aided Localization Detectors 155
5.1 Persymmetric Localization Detectors 155
5.1.1 Problem Formulation 156
5.1.2 Detector Designs 157
5.1.3 Illustrative Examples 161
5.2 Symmetric Spectrum Localization Detectors 170
5.2.1 Problem Formulation 170
5.2.2 Detector Designs 172
5.2.3 Illustrative Examples 174
5.3 Bayesian Localization Detectors 177
5.3.1 Problem Formulation 177
5.3.2 Detector Designs 180
5.3.3 Illustrative Examples 183
References 191
Appendix A: Complex Gaussian Distribution with Circular
Symmetry 193
Appendix B: The Equivalent form of Detector (3.25) 197
Appendix C: Derivations of the Distribution of q Defined in (3.33) 201
Appendix D: The Equivalent form of Detector (3.61) 203
Appendix E: The Proof of Proposition 3.2 207
Appendix F: The Proof of Proposition 3.4 209
Appendix G: Expressions of the Coefficients for (3.128) and (3.130) 211
Appendix H: The Proof of Proposition 3.5 213
Appendix I: The Correlation Model of the Clutter Returns 215
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