CONTENTS Chapter 1Preface Reference Chapter 2Classical Detection with Fixed Threshold 2.1Fundamental Problems and Principles of Radar Automatic Detection 2.1.1Maximum Detection Range 2.1.2False Alarm Rate 2.1.3Swerlingfluctuation Models of Target Radar Cross Section 2.1.4Classical Issue of Automatic Detection—the Detection with Fixed Threshold 2.2Matched Filtering 2.2.1Matched Filtering in White Gaussian Noise Background 2.2.2Matched Filtering and Correlated Receiving 2.2.3Matched Filter for Coherent Pulsetrain Signals 2.3SinglePulse Detection 2.3.1SinglePulse Linear Detection for Nonfluctuation Target 2.3.2SinglePulse Linear Detection for Swerlingfluctuation Target 2.4MultiplePulse Detection 2.4.1Binary Detection 2.4.2Linear Detection 2.4.3Detection of Coherent PulseTrain Signals 2.5Summary Reference Chapter 3The CFAR Processing Methods Based on Mean Level 3.1Introduction 3.2Description of Basic Models 3.3CACFAR Detector 3.4GO and SOCFAR Detector 3.5WCACFAR Detector 3.6CACFAR Scheme with LogarithmicLaw Detector 3.7CACFAR Scheme with SinglePulse Linear Detector 3.8CACFAR Detector for Multiple Pulses 3.8.1CACFAR Detector with Double Threshold 3.8.2CACFAR Detector based on Multiple Pulses Noncoherent Accumulation 3.9Performance of MLCFAR Detectors in Homogeneous Background 3.10Performance of MLCFAR Detectors in Multiple Target Situations 3.11Performance of MLCFAR Detectors at Clutter Edges 3.12Comparison and Summary Reference Chapter 4The CFAR Processing Methods Based on Order Statistics 4.1Introduction 4.2Description of Basic Models 4.3OSCFAR Detector 4.4CMLDCFAR Detector 4.5TMCFAR Detector 4.6MXCMLD CFAR Detector 4.7OSGOCFAR and OSSOCFAR Detectors 4.8SCFAR Detector 4.9Other CFAR Detectors based on Order Statistics 4.9.1CATMCFAR Detector 4.9.2SOSGOCFAR and MSCFAR Detectors 4.10Performance of OrderStatistic CFAR Detectors 4.10.1Performance in Homogeneous Background 4.10.2Performance in Multiple Target Situations 4.10.3Performance at Clutter Edges 4.11Comparison and Summary Reference
Chapter 5The Generalized OrderStatistic (GOS) CFAR Detectors with Automatic Censoring Technique 5.1Introduction 5.2Description of Basic Models 5.2.1Model Description of OSOS Type CFAR Detectors 5.2.2Model Description of OSCA Type CFAR Detectors 5.2.3Model Description of TMTM Type CFAR Detectors 5.3GOSCA,GOSGO,GOSSOCFAR Detectors 5.3.1GOSCACFAR Detector 5.3.2GOSGOCFAR Detector 5.3.3GOSSOCFAR Detector 5.4MOSCA,OSCAGO,OSCASOCFAR Detectors 5.4.1MOSCACFAR Detector 5.4.2OSCAGOCFAR Detector 5.4.3OSCASOCFAR Detector 5.5MTM,TMGO,TMSOCFAR Detectors 5.5.1MTMCFAR Detector 5.5.2TMGOCFAR Detector 5.5.3TMSOCFAR Detector
5.6Performance of GOS Type CFAR Detectors in Homogeneous Background and Multiple Target Situations 5.6.1Performance of GOS Type CFAR Detectors in Homogeneous Background 5.6.2Performance of GOS Type CFAR Detectors in Multiple Target Situations 5.7Performance of GOS Type CFAR Detectors at Clutter Edges 5.7.1Performance of GOSCACFAR Detectors at Clutter Edges 5.7.2Performance of GOSGO,GOSSOCFAR Detectors at Clutter Edges 5.7.3Performance of MOSCACFAR Detectors at Clutter Edges 5.7.4Performance of OSCAGO,OSCASOCFAR Detectors at Clutter Edges 5.7.5Performance of MTM,TMGOCFAR Detectors at Clutter Edges 5.8Comparison and Summary Reference Chapter 6Adaptive CFAR Detectors 6.1Introduction 6.2CCACFAR Detector 6.3HCECFAR Detector 6.4ECFAR Detector 6.4.1ECFAR Detector Architecture 6.4.2Performance of ECFAR Detector in Homogeneous Background 6.4.3Performance of ECFAR Detector in Multiple Target Situations 6.5OSTACFAR Detector 6.5.1Principle of OSTACFAR Detector 6.5.2Performance of OSTACFAR Detector in Clutter Edge 6.5.3Performance of OSTACFAR Detector in Multiple Target Situations 6.6VTMCFAR Detector 6.6.1Principle of VTMCFAR Detector 6.6.2Performance of VTMCFAR Detector in Homogeneous Background 6.6.3Performance of VTMCFAR Detector in Multiple Target Situations 6.6.4Performance of VTMCFAR Detector in Clutter Edge 6.6.5Choice of Parameters for VTMCFAR Detector 6.7A Series of CFAR Detectors of Himonas 6.7.1GCMLDCFAR Detector 6.7.2GO/SOCFAR Detector 6.7.3ACMLDCFAR Detector 6.7.4GTLCMLDCFAR Detector 6.7.5ACGOCFAR Detector 6.8VICFAR Detector 6.8.1Application of VICFAR Detector in Different Background 6.8.2Performance Analysis of VICFAR Detector 6.9ESECA CFAR Detector 6.9.1ESECA method 6.9.2Simulation Analysis of Detection Performance 6.10Other Adaptive CFAR Detectors 6.10.1Double Adaptive CFAR Detector 6.10.2ACCFAR Detector 6.10.3Improved CACFAR Detector 6.10.4Adaptive Length CFAR Detector 6.10.5ACCAODVCFAR Detector 6.11Comparison and Summary Reference Chapter 7The CFAR Detectors in Classical nonGaussian Background 7.1Introduction 7.2Logt CFAR Detector 7.2.1Logt CFAR Detector in Lognormal Distribution 7.2.2Logt CFAR Detector in Weibull Distribution 7.3OrderStatistic CFAR Detectors in Weibull Background 7.3.1Detection Performance of OSCFAR Detector in Weibull Background 7.3.2Detection Performance of OSGOCFAR Detector in Weibull Background 7.3.3WeberHaykin CFAR Scheme in Weibull Background 7.3.4Estimation of c Based on Expectation and Median of Reference Samples 7.3.5Detection Performance of OSCFAR with Binary Integration for Multiple Pulses 7.3.6Detection Performance of OSGOCFAR with Binary Integration for Multiple Pulses 7.4MLHCFAR Detector 7.4.1MLHCFAR Detector in Weibull Background with Known Shape Parameter 7.4.2MLHCFAR Detector in Weibull Background with Unknown Shape Parameter 7.4.3Detection Probability and CFAR Loss 7.5BLUECFAR Detector 7.5.1BLUE in Weibull Background 7.5.2BLUE in Lognormal Background 7.6CFAR Detectors in Pearson Distribution 7.6.1CACFAR Detectors in Pearson Distribution 7.6.2OSCFAR Detectors in Pearson Distribution 7.6.3CMLDCFAR Detectors in Pearson Distribution 7.7CFAR Detector in Cauchy Distribution 7.8Comparison and Summary Reference Chapter 8CFAR Processing in Compound Gaussian Clutter 8.1Introduction 8.2Compound Gaussian Distribution 8.2.1Compound Gaussian Complex Amplitude Model 8.2.2K Distributed Envelop Clutter Model 8.2.3Correlated K Distributed Clutter Model 8.2.4Simulation of K Distributed Clutter 8.3Detection Performance in K Distributed Clutter plus Thermal Noise 8.3.1Matching of K Distribution with Recorded Data 8.3.2Calculation of Detection Performance in Clutter plus Noise 8.3.3Performance Analysis 8.4Performance Analysis of Classical CFAR Detectors in K Distributed Clutter 8.4.1CFAR Detection in K Distributed Clutter with Uncorrelated Modulation Process 8.4.2CFAR Detection in K Distributed Clutter with Completely Correlated Modulation Process 8.4.3CFAR Detection in K Distributed Clutter with Partially Correlated Modulation Process 8.5Optimal CFAR Detectors in Compound Gaussian Clutter 8.5.1Optimal CFAR Detectors in Compound Gaussian Clutter Envelop 8.5.2Optimal Coherent Subspace CFAR Detectors in Compound Gaussian Clutter 8.6Coherent CFAR Detectors in Spherically Invariant Random Clutter 8.6.1Maximum Likelihood Estimation Problem 8.6.2CFAR Detection Problem 8.6.3Performance Analysis 8.7Bayesian Adaptive Detector in Compound Gaussian Clutter 8.7.1Problem Formulation 8.7.2Design of Bayesian Adaptive Detector 8.7.3Performance Analysis 8.8Summary Reference Chapter 9Nonparametric CFAR Detection 9.1Introduction 9.2Asymptotic Relative Efficiency for Nonparametric Detector 9.3OneSample Nonparametric Detector 9.3.1Sign Detector 9.3.2Wilcoxon Detector 9.4TwoSample Nonparametric Detector 9.4.1Generalized Sign Detector 9.4.2MannWhitney Detector 9.4.3Savage Detector and Modifier 9.4.4Rank Squared Detector and Modifier 9.4.5Asymptotic Relative Efficiency of Several Nonparametric Detectors 9.4.6Detection Performance of Nonparametric Detector with Finite Samples 9.5Suboptimal Rank Nonparametric Detector 9.5.1Locally Optimal Rank Detector 9.5.2Suboptimal Rank Detector 9.5.3Performance Analysis 9.6Performance Analysis of Nonparametric Detectors in Weibull Clutter 9.6.1Rank Quantization Nonparameter Detector in Weibull Clutter 9.6.2Generalized Sign Nonparameter Detector in Weibull Clutter 9.7Nonparametric Detectors Using InverseNormalScore Function Modified Rank 9.7.1Basic Design Idea 9.7.2Detector Design 9.7.3Performance Analysis 9.8Comparison and Summary Reference Chapter 10Clutter Map CFAR Processing 10.1Introduction 10.2Nitzbergs Clutter Map Technique 10.2.1Principle of Nitzbergs Clutter Map 10.2.2Restriction on w by the ADT and False Alarm Rate of Nitzbergs Clutter Map 10.2.3Performance of Nitzbergs Clutter Map in Weibull Clutter 10.3Clutter Map CACFAR PlaneDetection Technique 10.3.1Basic Model Description 10.3.2Performance Analysis in Homogeneous Background 10.3.3Performance Comparison between PlaneDetection and PointDetection 10.4Hybrid CM/LCFAR Clutter Map Detection Technique 10.4.1Basic Model 10.4.2Performance in Homogeneous Background 10.4.3Performance in the Situations with Interference Target 10.5Biparametric Clutter Map Detection Technique 10.5.1Basical Model of Biparametric Clutter Map 10.5.2Target Selfmasking Avoidance 10.6Comparison and Summary Reference Chapter 11CFAR Processing in Transform Domain 11.1Introduction 11.2Transform Domain CFAR 11.2.1Discrete Fourier Transform of Signal,Clutter and Noise 11.2.2Frequency Domain CACFAR 11.2.3MTIFFTfrequency Domain CACFAR 11.2.4Frequency Domain Oddeven Processing Detector 11.3Wavelet domain CFAR 11.3.1CMCFAR Based on Discrete Wavelet Transform 11.3.2CACFAR Based on Orthogonal Wavelet Transform 11.4Fractional Fourier Transform Domain Target Detection 11.4.1LFM Signal Detection and Estimation via FRFT 11.4.2Moving Target Detector in FRFT Domain 11.4.3Longtime Coherent Integration in FRFT Domain 11.5HilbertHuang Transform Domain Target Detection 11.5.1Principle of HHT 11.5.2Weak Target Detection Based on IMF Property 11.6Sparse representation domain target detection 11.6.1Signal Sparse Representation Model and Solution 11.6.2Radar Target Detection Based on Sparse Timefrequency Distribution 11.6.3Radar Target Detection Result and Analysis 11.7Summary Reference Chapter 12Target Detection for High Resolution Radar 12.1Introduction 12.2Signal Model of RangeSpread Target 12.2.1Rank One Signal Model 12.2.2MultiRank Subspace Signal Model 12.3MultiRank Subspace Detector of RangeSpread Target in Compound Gaussian Clutter 12.3.1Problem Formulation 12.3.2Design of Generalized Matched Subspace Detector 12.3.3Calculation of Probability of False Alarm for Generalized Matched Subspace Detector 12.3.4Adaptive Implementation of Generalized Matched Subspace Detector 12.3.5Performance Analysis 12.4RangeSpread Target Detector in Compound Gaussian Clutter plus Thermal Noise 12.4.1Problem Formulation 12.4.2Equivalent Processing of Thermal Noise 12.4.3Design of RangeSpread Target Detector in Compound Gaussian Clutter plus Thermal Noise 12.4.4Detection Performance Analysis 12.5Detector of RangeSpread Target in SαS Clutter 12.5.1SαS Distribution and PFLOM Transform 12.5.2Problem Formulation 12.5.3RangeSpread Target Detector based on PFLOM Transform 12.5.4Binary Integration Cauchy Detector in SαS Clutter 12.6Main Aspects of CFAR Detection for SAR Images and Selection of Clutter Cells 12.6.1Main Aspects of CFAR Detection for SAR Images 12.6.2Selection of Clutter Cells for SAR Images in CFAR Detection 12.7CFAR Detection for SAR Images based on Generalized Gamma Clutter Model 12.7.1Detector Design 12.7.2Performance Analysis 12.8Semantic Knowledgeaided CFAR Detection for SAR Images 12.8.1Detector Design 12.8.2Performance Analysis 12.9Fast Implementation based on Density Character of CFAR Detection for SAR Images 12.9.1Detector Design 12.9.2Performance Analysis 12.10Comparison and Summary Reference Chapter 13Distributed CFAR Processing with Multisensor 13.1Introduction 13.2Distributed CFAR Detection with Multisensor based on Local Binary Decision 13.2.1Distributed CACFAR Detection 13.2.2Distributed OSCFAR Detection 13.2.3Examples for Distributed CFAR Detection 13.3Distributed CFAR Detection with Multisensor based on Local Test Statistic 13.3.1Distributed CFAR Detection based on R Type Local Test Statistic 13.3.2Distributed CFAR Detection based on S Type Local Test Statistic 13.4CFAR Detection of Distributed MIMO Radar 13.4.1the Classical Linear Model of Target Returns and Detector Design 13.4.2Performance Analysis of AMF Detector for Distributed MIMO Apertures 13.4.3Simulation and Analysis 13.5Summary Reference Chapter 14Multidimensional CFAR Processing 14.1Introduction 14.2CFAR Detection for Array Radar 14.2.1Signal Model and Binary Hypothesis Test 14.2.2Array Radar Detector with Rank1 Target Model 14.2.3Array Radar Detector with Subspace Target Model 14.2.4Property and Performance of Array Radar Target Detector 14.3Twodimension CFAR Detection based on Adaptive Spacetime Coding Design 14.3.1Signal Model and MSD Detector 14.3.2Adaptive Spacetime Coding Design 14.3.3Simulation and Analysis 14.4Spacetimerange Adaptive Detection 14.4.1MIMO Radar Signal Model 14.4.2Spacetimerange Adaptive Processing after Matched Filtering 14.4.3Spacetimerange Adaptive Processing 14.4.4Implementation and Fast Matrix Update 14.4.5Adaptive Focus and Detection Integrated Processing 14.4.6Simulation and Analysis 14.5Other Multidimensional CFAR Detection 14.5.1CFAR Detection with ScantoScan Fusion 14.5.2Polarimetric CFAR Processing 14.6Summary Reference Chapter 15CFAR Processing Based on Feature 15.1Introduction 15.2Fractal Feature of Sea Clutter in Time Domain and CFAR Detection 15.2.1Judge of Sea Spike 15.2.2Parameter of Sea Spike and Statistics 15.2.3Paretian Possion Model of Sea Spike 15.2.4Target Detection and Performance Analysis 15.3Fractal Feature of Sea Clutter in Frequency Domain and CFAR Detection 15.3.1Fractal Property of FBM in Frequency Domain 15.3.2Monofractal Property of Sea Clutter Frequency Spectrum 15.3.3Influence Factor of Sea Clutter Monofractal Parameter 15.3.4Target Detection and Performance Analysis 15.4Multifeature of Sea Clutter in Time/Frequency Domain and Target Detection 15.4.1Feature Extraction and Analysis 15.4.2Detector Using Three Features 15.4.3Detection Performance Analysis 15.5Target Detection Based on Deep Learning 15.5.1Integration of Pulse Compression and Detection based on RNN 15.5.2Simulation and Analysis 15.5.3Verification Using Measured Data 15.6Conclusion Reference Chapter 16Review,Suggestion and Prospect 16.1Review 16.1.1Foundation of Theory System of CFAR Processing 16.1.2Proposal of GOS Type CFAR Detectors with Automatic Censoring Technique and Foundation of Uniform Model 16.1.3Expand Adaptive CFAR Processing 16.1.4Develop Distributed CFAR Detection with Multisensor 16.1.5Expand CFAR Processing from Time and Frequency Domain to other Transform Domains 16.1.6Expand the Information Source Dimension of CFAR Processing from One to Many, and Form Multidimensional CFAR Detection 16.1.7Expand the Amplitude Feature to Multiple Feature including Fractal Feature 16.2Problems and Suggestions 16.2.1Performance Analysis and Evaluation Methods 16.2.2Strengthen the Research on Target Characteristics 16.2.3Expand the Research ideas about CFAR 16.2.4Pay Attention to the CFAR Processing Research in the New System Radar 16.3Prospect for Research Direction 16.3.1Multidimensional Signal CFAR Processing 16.3.2Background Clutter Identification and Intelligent Processing 16.3.3Application of New Signal Processing Method and Multifeature CFAR Processing 16.3.4CFAR Processing in Other Areas Reference English Abbreviation Glossary
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