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《自适应雷达信号检测与距离估计（英文版）》系统介绍了雷达信号检测领域的发展前沿和研究成果，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，《自适应雷达信号检测与距离估计（英文版）》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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Contents1 Introduction to Radar Systems 11.1 Historical Background 11.2 Pulsed Radar Architectures 41.3 An Introduction to Design Parameters 81.3.1 The Ambiguity Function 101.3.2 Doppler Resolution and the Pulse Burst Waveform 141.3.3 Radar Equation 191.4 Organization and Outline of the Book 20References 212 Adaptive Radar Detection: Classical Approach 232.1 Analytical Models for Target and Interference 242.2 Decision Theory in Radar 302.2.1 Hypothesis Testing Problems 302.2.2 Design Criteria 342.3 Conventional Detectors for Point-Like Targets 382.3.1 Decision Rules 382.3.2 CFAR Property 42References 433 Knowledge-Aided Detectors 453.1 Persymmetric Detectors 463.1.1 Problem Formulation 463.1.2 Detector Designs 483.1.3 Illustrative Examples 613.2 Symmetric Spectrum Detectors 723.2.1 Problem Formulation 733.2.2 Detector Designs 753.2.3 Illustrative Examples 843.3 Joint Exploitation of Persymmetry and Symmetry 903.3.1 Problem Formulation 903.3.2 Detector Designs 933.3.3 Illustrative Examples 96References 1004 Detectors with Enhanced Range Estimation Capabilities 1034.1 Localization Detectors for Point-Like Targets 1044.1.1 Problem Formulation 1044.1.2 Detector Designs 1064.1.3 Illustrative Examples 1134.2 Polarimetric Localization Detectors 1204.2.1 Problem Formulation 1214.2.2 Detector Designs 1224.2.3 Illustrative Examples 1274.3 Oversampling Localization Detectors 1344.3.1 Problem Formulation 1354.3.2 Detector Designs 1394.3.3 Illustrative Examples 146References 1525 Knowledge-Aided Localization Detectors 1555.1 Persymmetric Localization Detectors 1555.1.1 Problem Formulation 1565.1.2 Detector Designs 1575.1.3 Illustrative Examples 1615.2 Symmetric Spectrum Localization Detectors 1705.2.1 Problem Formulation 1705.2.2 Detector Designs 1725.2.3 Illustrative Examples 1745.3 Bayesian Localization Detectors 1775.3.1 Problem Formulation 1775.3.2 Detector Designs 1805.3.3 Illustrative Examples 183References 191Appendix A: Complex Gaussian Distribution with CircularSymmetry 193Appendix B: The Equivalent form of Detector (3.25) 197Appendix C: Derivations of the Distribution of q Defined in (3.33) 201Appendix D: The Equivalent form of Detector (3.61) 203Appendix E: The Proof of Proposition 3.2 207Appendix F: The Proof of Proposition 3.4 209Appendix G: Expressions of the Coefficients for (3.128) and (3.130) 211Appendix H: The Proof of Proposition 3.5 213Appendix I: The Correlation Model of the Clutter Returns 215
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