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Informationen zum Autor Graham V. Weinberg completed his B.S. and Ph.D. degrees at the University of Melbourne, Australia. His doctoral thesis examined distributional approximations of stochastic processes using the Stein-Chen method. After a short period in telecommunications research at the University of Adelaide, he joined Defence Science and Technology Group, Australia. In the capacity of a scientist, he has undertaken research into radar detection issues arising from airborne high resolution X-band maritime surveillance platforms. To further continue his professional development, he has also completed a Master’s degree in signal and information processing through the University of Adelaide, Australia. His research interests include CFAR, coherent multi-look radar detection and the mathematics of radar signal processing. He has published extensively and is a member of the Institution of Engineering and Technology (IET), UK. Klappentext This book outlines and examines recent developments of high resolution X-band maritime surveillance radar. Performance is assessed when the detectors are run in real X-band radar clutter. The book introduces relevant mathematical tools to allow the reader to understand the development, and follow its implementation. Zusammenfassung This book outlines and examines recent developments of high resolution X-band maritime surveillance radar. Performance is assessed when the detectors are run in real X-band radar clutter. The book introduces relevant mathematical tools to allow the reader to understand the development, and follow its implementation. Inhaltsverzeichnis SECTION I: PRELIMINARIESIntroductionPurposeSliding Window DetectorsRange-Time Intensity ExampleHistorical DevelopmentMathematical FormulationDetectors in Exponentially Distributed ClutterSome Fundamental ConceptsStructure of the BookProbability and Distribution Theory for Radar DetectionOutlineFundamentals of ProbabilityTransformationsMomentsInequalitiesJointly Distributed Random VariablesConditional DistributionsSome Special Functions of Random VariablesOrder StatisticsUniform Distributions and SimulationProperties of EstimatorsSpherically Invariant Random ProcessesDistributions for X-Band Maritime Surveillance Radar ClutterIntroductionEarly Models for ClutterThe Weibull DistributionK-DistributionThe Pareto Class of DistributionsPareto Type DistributionsProperties of the Pareto DistributionParameter EstimationPareto Model Adopted for Detector DevelopmentSECTION II: FUNDAMENTAL DETECTION PROCESSESAdaptation of Exponential Detectors to Pareto Type I Distributed ClutterIntroductionGeneral ConsiderationsThe Order Statistic DetectorThe Cell-Averaging DetectorThe Geometric Mean DetectorPerformance in Homogeneous ClutterEffect of Interfering TargetsClutter TransitionsConclusionsA Transformation Approach for Radar Detector DesignIntroductionThe Transformation ApproachExamples of Detector PerformancePreservation of the CFAR PropertyLomax-Distributed Clutter and Detector PerformanceModification of the General Transformed DetectorSpecialisation to the Pareto Clutter CasePerformance of the New CFAR ProcessesModified Minimum Order Statistic DetectorIntroductionTransformed Order Statistic DetectorsDetector ComparisonMathematical Analysis of DetectorsSelection of Parameter MPerformance in Homogeneous ClutterExamples of Management of InterferenceFalse Alarm RegulationConclusionsDual Order Statistic CFAR DetectorsIntroductionMotivation and Definition of Detection ProcessSpecialisation to the Pareto Type I CasePerformance in Homogeneous ClutterManagement of Interfering TargetsFalse Alarm RegulationConclusionsOn Goldstein's Log-t DetectorIntroductionThe Log-t DetectorAn Order Statistic Based Log-t DetectorPerformance in Homogeneous ClutterInterferenceFalse Alarm RegulationConclusionsSECTION III: SPECIALISED D...
