Signal Processing in Radar Systems

An essential task in radar systems is to find an appropriate solution to the problems related to robust signal processing and the definition of signal parameters. Signal Processing in Radar Systems addresses robust signal processing problems in complex radar systems and digital signal processing subsystems. It also tackles the important issue of defining signal parameters. The book presents problems related to traditional methods of synthesis and analysis of the main digital signal processing operations. It also examines problems related to modern methods of robust signal processing in noise, with a focus on the generalized approach to signal processing in noise under coherent filtering. In addition, the book puts forth a new problem statement and new methods to solve problems of adaptation and control by functioning processes. Taking a systems approach to designing complex radar systems, it offers readers guidance in solving optimization problems. Organized into three parts, the book first discusses the main design principles of the modern robust digital signal processing algorithms used in complex radar systems. The second part covers the main principles of computer system design for these algorithms and provides real-world examples of systems. The third part deals with experimental measurements of the main statistical parameters of stochastic processes. It also defines their estimations for robust signal processing in complex radar systems. Written by an internationally recognized professor and expert in signal processing, this book summarizes investigations carried out over the past 30 years. It supplies practitioners, researchers, and students with general principles for designing the robust digital signal processing algorithms employed by complex radar systems.

IntroductionPart I Design of Radar Digital Signal Processing and Control AlgorithmsPrinciples of Systems Approach to Design Complex Radar SystemsMethodology of Systems ApproachMain Requirements to Complex Radar SystemsProblems of System Design for Automated Complex Radar SystemsRadar Signal Processing System as an Object of DesignSignal Processing by Digital Generalized Detector in Complex Radar SystemsAnalog to Digital Signal Conversion: Main PrinciplesDigital Generalized Detector for Coherent Impulse SignalsConvolution in Time DomainConvolution in Frequency DomainExamples of Some DGD TypesDigital Interperiod Signal Processing AlgorithmsDigital Moving-Target Indication AlgorithmsDGD for Coherent Impulse Signals with Known ParametersDGD for Coherent Impulse Signals with Unknown ParametersDigital Measurers of Target Return Signal ParametersComplex Generalized Algorithms of Digital Interperiod Signal ProcessingAlgorithms of Target Range Track Detection and TrackingMain Stages and Signal Reprocessing OperationsTarget Range Track Detection Using Surveillance Radar DataTarget Range Tracking Using Surveillance Radar DataFiltering and Extrapolation of Target Track Parameters Based on Radar MeasureInitial ConditionsProcess Representation in Filtering SubsystemsStatistical Approach to Solution of Filtering Problems of Stochastic (Unknown) ParametersAlgorithms of Linear Filtering and Extrapolation under Fixed Sample Size of MeasurementsRecurrent Filtering Algorithms of Undistorted Polynomial Target Track ParametersAdaptive Filtering Algorithms of Maneuvering Target Track ParametersLogical Flowchart of Complex Radar Signal Reprocessing AlgorithmPrinciples of Control Algorithm Design for Complex Radar System Functioning at Dynamical ModeConfiguration and Flowchart of Radar Control SubsystemDirect Control of Complex Radar Subsystem ParametersScan Control in New Target Searching ModePower Resource Control under Target TrackingDistribution of Power Resources of Complex Radar System under Combination of Target Searching and Target Tracking ModesPart II Design Principles of Computer System for Radar Digital Signal Processing and Control AlgorithmsDesign Principles of Complex Algorithm Computational Process in Radar SystemsDesign ConsiderationsComplex Algorithm AssignmentEvaluation of Work Content of Complex Digital Signal Processing Algorithm Realization by Microprocessor SubsystemsParalleling of Computational ProcessDesign Principles of Digital Signal Processing Subsystems Employed by Complex Radar SystemStructure and Main Engineering Data of Digital Signal Processing SubsystemsRequirements for Effective Speed of OperationRequirements for RAM Size and StructureSelection of Microprocessor for Designing the Microprocessor SubsystemsStructure and Elements of Digital Signal Processing and Complex Radar System Control Microprocessor SubsystemsHigh-Performance Centralized Microprocessor Subsystem for Digital Signal Processing of Target Return Signals in Complex Radar SystemsProgrammable Microprocessor for Digital Signal Preprocessing of Target Return Signals in Complex Radar SystemsDigital Signal Processing Subsystem Design (Example)General StatementsDesign of Digital Signal Processing and Control Subsystem StructureStructure of Coherent Signal Preprocessing Microprocessor SubsystemStructure of Noncoherent Signal Preprocessing Microprocessor SubsystemSignal Reprocessing Microprocessor Subsystem SpecificationsStructure of Digital Signal Processing SubsystemGlobal Digital Signal Processing System AnalysisDigital Signal Processing System DesignAnalysis of "n – 1 – 1" MTI SystemAnalysis of "n – n – 1" MTI SystemAnalysis of "n – m – 1" MTI SystemComparative Analysis of Target Tracking SystemsPart III Stochastic Processes Measuring in Radar SystemsMain Statements of Statistical Estimation TheoryMain Definitions and Problem StatementPoint Estimate and Its PropertiesEffective EstimationsLoss Function and Average RiskBayesian Estimates for Various Loss FunctionsEstimation of Mathematical ExpectationConditional FunctionalMaximum Likelihood Estimate of Mathematical ExpectationBayesian Estimate of Mathematical Expectation: Quadratic Loss FunctionApplied Approaches to Estimate the Mathematical ExpectationEstimate of Mathematical Expectation at Stochastic Process SamplingMathematical Expectation Estimate under Stochastic Process Amplitude QuantizationOptimal Estimate of Varying Mathematical Expectation of Gaussian Stochastic ProcessVarying Mathematical Expectation Estimate under Stochastic Process Averaging in TimeEstimate of Mathematical Expectation by Iterative MethodsEstimate of Mathematical Expectation with Unknown PeriodEstimation of Stochastic Process VarianceOptimal Variance Estimate of Gaussian Stochastic ProcessStochastic Process Variance Estimate under Averaging in TimeErrors under Stochastic Process Variance EstimateEstimate of Time-Varying Stochastic Process VarianceMeasurement of Stochastic Process Variance in NoiseEstimation of Probability Distribution and Density Functions of Stochastic ProcessMain Estimation RegularitiesCharacteristics of Probability Distribution Function EstimateVariance of Probability Distribution Function EstimateCharacteristics of the Probability Density Function EstimateProbability Density Function Estimate Based on Expansion in Series Coefficient EstimationsMeasurers of Probability Distribution and Density Functions: Design PrinciplesEstimate of Stochastic Process Frequency-Time ParametersEstimate of Correlation FunctionCorrelation Function Estimation Based on its Expansion in SeriesOptimal Estimation of Gaussian Stochastic Process Correlation Function ParameterCorrelation Function Estimation Methods Based on Other PrinciplesSpectral Density Estimate of Stationary Stochastic ProcessEstimate of Stochastic Process Spike ParametersMean-Square Frequency Estimate of Spectral DensityNotation IndexIndex Chapters include a summary and discussion as well as references.

Dr. Vyacheslav Tuzlukov is currently a full professor in the Department of Information Technologies and Communication, School of Electronics Engineering, College of IT Engineering, Kyungpook National University, Daegu, South Korea. He is an author of over 170 journal and conference papers and eight books on signal processing, including Signal Processing Noise (CRC Press, 2002) and Signal and Image Processing in Navigational Systems (CRC Press, 2004). He is a keynote speaker, chair of sessions, tutorial instructor, and plenary speaker at major international conferences on signal processing. Dr. Tuzlukov has been highly recommended by U.S. experts of Defense Research and Engineering (DDR&E) of the United States Department of Defense (U.S. DoD) for his expertise in the field of humanitarian demining and minefield-sensing technologies and was awarded the Special Prize of the U.S. DoD in 1999. His achievements have distinguished him as one of the leading experts from around the world by Marquis Who’s Who.