Signal Processing in Radar Systems: 1st Edition (Paperback) book cover

Signal Processing in Radar Systems

1st Edition

By Vyacheslav Tuzlukov

CRC Press

632 pages | 197 B/W Illus.

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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.

Table of Contents


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


Chapters include a summary and discussion as well as references.

About the Author

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.

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