●1 Introduction to Radar Systems
1.1 Historical Background
1.2 Pulsed Radar Architectures
1.3 An Introduction to Design Parameters
1.3.1 The Ambiguity Function
1.3.2 Doppler Resolution and the Pulse Burst Waveform
1.3.3 Radar Equation
1.4 Organization and Outline of the Book
References
2 Adaptive Radar Detection: Classical Approach
2.1 Analytical Models for Target and Interference
2.2 Decision Theory in Radar
2.2.1 Hypothesis Testing Problems
2.2.2 Design Criteria
2.3 Conventional Detectors for Point-Like Targets
2.3.1 Decision Rules
2.3.2 CFAR Property
References
3 Knowledge-Aided Detectors
3.1 Persymmetric Detectors
3.1.1 Problem Formulation
3.1.2 Detector Designs
3.1.3 Illustrative Examples
3.2 Symmetric Spectrum Detectors
3.2.1 Problem Formulation
3.2.2 Detector Designs
3.2.3 Illustrative Examples
3.3 Joint Exploitation of Persymmetry and Symmetry
3.3.1 Problem Formulation
3.3.2 Detector Designs
3.3.3 Illustrative Examples
References
Detectors with Enhanced Range Estimation Capabilities
4.1 Localization Detectors for Point-Like Targets
4.1.1 Problem Formulation
4.1.2 Detector Designs
4.1.3 Illustrative Examples
4.2 Polarimetric Localization Detectors
4.2.1 Problem Formulation
4.2.2 Detector Designs
4.2.3 Illustrative Examples
4.3 Oversampling Localization Detectors
4.3.1 Problem Formulation
4.3.2 Detector Designs
4.3.3 Illustrative Examples
References
5 Knowledge-Aided Localization Detectors
5.1 Persymmetric Localization Detectors
5.1.1 Problem Formulation
5.1.2 Detector Designs
5.1.3 Illustrative Examples
5.2 Symmetric Spectrum Localization Detectors
5.2.1 Problem Formulation
5.2.2 Detector Designs
5.2.3 Illustrative Examples
5.3 Bayesian Localization Detectors
5.3.1 Problem Formulation
5.3.2 Detector Designs
5.3.3 Illustrative Examples
References
Appendix A: Complex Ganssian Distribution with Circular
Symmetry
Appendix B: The Equivalent form of Detector (3.25 )
Appendix C: Derivations of the Distribution of ~ Defined in (3.33 )
Appendix D: The Equivalent form of Detector (3.61 )
Appendix G: Expressions of the Coefficients for (3.128) and (3.13 0) ..
Appendix I: The Correlation Model of the Clutter Returns
《自適應雷達信號檢測與距離估計（英文版）》繫統介紹了雷達信號檢測領域的發展前沿和近期新研究成果，重點闡述了知識基自適應檢測和洩露自適應檢測兩方面內容。對於知識基自適應檢測，包括陣列斜對稱檢測、雜波譜對稱檢測和貝葉斯檢測三部分內容，實現了對各種先驗知識的有效利用，大幅提高雷達在非均勻環境下的探測性能。對於洩露自適應檢測，在完成離散時間信號建模基礎上，構建了相假設檢驗問題，采用廣義似然比等檢驗準則給出解決方案，將以洩露目標能量創新地加以利用，不僅有效減小洩露損失，還實現了對目標距離的有效估計。進一步探討了提高洩露檢測性能的措施，包括對時間序列進行過采樣、利用前述各類先驗知識等。此外，《自適應雷達信號檢測與距離估計（英文版）》還采用雷達實測數據對所介紹方法的有效性進行了充分驗證。
