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.
Vyacheslav Tuzlukov (Kyungpook National University Daegu South Korea)
CRC Press Inc
Country of Publication:
26 October 2012
Introduction Part I Design of Radar Digital Signal Processing and Control Algorithms Principles of Systems Approach to Design Complex Radar Systems Methodology of Systems Approach Main Requirements to Complex Radar Systems Problems of System Design for Automated Complex Radar Systems Radar Signal Processing System as an Object of Design Signal Processing by Digital Generalized Detector in Complex Radar Systems Analog to Digital Signal Conversion: Main Principles Digital Generalized Detector for Coherent Impulse Signals Convolution in Time Domain Convolution in Frequency Domain Examples of Some DGD Types Digital Interperiod Signal Processing Algorithms Digital Moving-Target Indication Algorithms DGD for Coherent Impulse Signals with Known Parameters DGD for Coherent Impulse Signals with Unknown Parameters Digital Measurers of Target Return Signal Parameters Complex Generalized Algorithms of Digital Interperiod Signal Processing Algorithms of Target Range Track Detection and Tracking Main Stages and Signal Reprocessing Operations Target Range Track Detection Using Surveillance Radar Data Target Range Tracking Using Surveillance Radar Data Filtering and Extrapolation of Target Track Parameters Based on Radar Measure Initial Conditions Process Representation in Filtering Subsystems Statistical Approach to Solution of Filtering Problems of Stochastic (Unknown) Parameters Algorithms of Linear Filtering and Extrapolation under Fixed Sample Size of Measurements Recurrent Filtering Algorithms of Undistorted Polynomial Target Track Parameters Adaptive Filtering Algorithms of Maneuvering Target Track Parameters Logical Flowchart of Complex Radar Signal Reprocessing Algorithm Principles of Control Algorithm Design for Complex Radar System Functioning at Dynamical Mode Configuration and Flowchart of Radar Control Subsystem Direct Control of Complex Radar Subsystem Parameters Scan Control in New Target Searching Mode Power Resource Control under Target Tracking Distribution of Power Resources of Complex Radar System under Combination of Target Searching and Target Tracking Modes Part II Design Principles of Computer System for Radar Digital Signal Processing and Control Algorithms Design Principles of Complex Algorithm Computational Process in Radar Systems Design Considerations Complex Algorithm Assignment Evaluation of Work Content of Complex Digital Signal Processing Algorithm Realization by Microprocessor Subsystems Paralleling of Computational Process Design Principles of Digital Signal Processing Subsystems Employed by Complex Radar System Structure and Main Engineering Data of Digital Signal Processing Subsystems Requirements for Effective Speed of Operation Requirements for RAM Size and Structure Selection of Microprocessor for Designing the Microprocessor Subsystems Structure and Elements of Digital Signal Processing and Complex Radar System Control Microprocessor Subsystems High-Performance Centralized Microprocessor Subsystem for Digital Signal Processing of Target Return Signals in Complex Radar Systems Programmable Microprocessor for Digital Signal Preprocessing of Target Return Signals in Complex Radar Systems Digital Signal Processing Subsystem Design (Example) General Statements Design of Digital Signal Processing and Control Subsystem Structure Structure of Coherent Signal Preprocessing Microprocessor Subsystem Structure of Noncoherent Signal Preprocessing Microprocessor Subsystem Signal Reprocessing Microprocessor Subsystem Specifications Structure of Digital Signal Processing Subsystem Global Digital Signal Processing System Analysis Digital Signal Processing System Design Analysis of n - 1 - 1 MTI System Analysis of n - n - 1 MTI System Analysis of n - m - 1 MTI System Comparative Analysis of Target Tracking Systems Part III Stochastic Processes Measuring in Radar Systems Main Statements of Statistical Estimation Theory Main Definitions and Problem Statement Point Estimate and Its Properties Effective Estimations Loss Function and Average Risk Bayesian Estimates for Various Loss Functions Estimation of Mathematical Expectation Conditional Functional Maximum Likelihood Estimate of Mathematical Expectation Bayesian Estimate of Mathematical Expectation: Quadratic Loss Function Applied Approaches to Estimate the Mathematical Expectation Estimate of Mathematical Expectation at Stochastic Process Sampling Mathematical Expectation Estimate under Stochastic Process Amplitude Quantization Optimal Estimate of Varying Mathematical Expectation of Gaussian Stochastic Process Varying Mathematical Expectation Estimate under Stochastic Process Averaging in Time Estimate of Mathematical Expectation by Iterative Methods Estimate of Mathematical Expectation with Unknown Period Estimation of Stochastic Process Variance Optimal Variance Estimate of Gaussian Stochastic Process Stochastic Process Variance Estimate under Averaging in Time Errors under Stochastic Process Variance Estimate Estimate of Time-Varying Stochastic Process Variance Measurement of Stochastic Process Variance in Noise Estimation of Probability Distribution and Density Functions of Stochastic Process Main Estimation Regularities Characteristics of Probability Distribution Function Estimate Variance of Probability Distribution Function Estimate Characteristics of the Probability Density Function Estimate Probability Density Function Estimate Based on Expansion in Series Coefficient Estimations Measurers of Probability Distribution and Density Functions: Design Principles Estimate of Stochastic Process Frequency-Time Parameters Estimate of Correlation Function Correlation Function Estimation Based on its Expansion in Series Optimal Estimation of Gaussian Stochastic Process Correlation Function Parameter Correlation Function Estimation Methods Based on Other Principles Spectral Density Estimate of Stationary Stochastic Process Estimate of Stochastic Process Spike Parameters Mean-Square Frequency Estimate of Spectral Density Notation Index Index 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.