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.
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.
Biography
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.
