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自適應(yīng)雷達(dá)信號(hào)檢測(cè)與距離估計(jì)(英文版)

自適應(yīng)雷達(dá)信號(hào)檢測(cè)與距離估計(jì)(英文版)

定 價(jià):¥128.00

作 者: 郝程鵬等
出版社: 科學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 暫缺

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ISBN: 9787030716903 出版時(shí)間: 2022-03-01 包裝: 平裝膠訂
開(kāi)本: 16開(kāi) 頁(yè)數(shù): 218 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

  本書(shū)系統(tǒng)介紹了雷達(dá)信號(hào)檢測(cè)領(lǐng)域的發(fā)展前沿和**研究成果,重點(diǎn)闡述了知識(shí)基自適應(yīng)檢測(cè)和泄露自適應(yīng)檢測(cè)兩方面內(nèi)容。對(duì)于知識(shí)基自適應(yīng)檢測(cè),包括陣列斜對(duì)稱(chēng)檢測(cè)、雜波譜對(duì)稱(chēng)檢測(cè)和貝葉斯檢測(cè)三部分內(nèi)容,實(shí)現(xiàn)了對(duì)各種先驗(yàn)知識(shí)的有效利用,大幅提高雷達(dá)在非均勻環(huán)境下的探測(cè)性能。對(duì)于泄露自適應(yīng)檢測(cè),在完成離散時(shí)間信號(hào)建模基礎(chǔ)上,構(gòu)建了相應(yīng)的二元假設(shè)檢驗(yàn)問(wèn)題,采用廣義似然比等檢驗(yàn)準(zhǔn)則給出解決方案,將以泄露目標(biāo)能量創(chuàng)新地加以利用,不僅有效減小泄露損失,還實(shí)現(xiàn)了對(duì)目標(biāo)距離的有效估計(jì)。進(jìn)一步探討了提高泄露檢測(cè)性能的措施,包括對(duì)時(shí)間序列進(jìn)行過(guò)采樣、利用前述各類(lèi)先驗(yàn)知識(shí)等。此外,本書(shū)還采用雷達(dá)實(shí)測(cè)數(shù)據(jù)對(duì)所介紹方法的有效性進(jìn)行了充分驗(yàn)證。

作者簡(jiǎn)介

暫缺《自適應(yīng)雷達(dá)信號(hào)檢測(cè)與距離估計(jì)(英文版)》作者簡(jiǎn)介

圖書(shū)目錄

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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