Adaptive Radar Signal Processing,9780471735823

Adaptive Radar Signal Processing

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Edition: 1st
ISBN13: 9780471735823
ISBN10: 0471735825
Format: Hardcover
Pub. Date: 2006-11-10
Publisher(s): Wiley-Interscience
List Price: $162.08

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Summary

This collaborative work presents the results of over twenty years of pioneering research by Professor Simon Haykin and his colleagues, dealing with the use of adaptive radar signal processing to account for the nonstationary nature of the environment. These results have profound implications for defense-related signal processing and remote sensing. References are provided in each chapter guiding the reader to the original research on which this book is based.

Author Biography

SIMON HAYKIN, PhD, is Distinguished University Professor in the Department of Electrical and Computer Engineering at McMaster University. He has pioneered signal-processing techniques and systems for radar and communication applications, and authored several acclaimed textbooks. Dr. Haykin has received numerous awards for his research including Honorary Doctor of Technical Sciences from ETH Zurich, Switzerland, and the first International Union of Radio Science Henry Booker Gold Medal.

Table of Contents

Preface xi
Contributors List xiii
1. Introduction 1(10)
Simon Haykin
Experimental Radar Facilities
2(3)
Organization of the Book
5(6)
Part I Radar Spectral Analysis
2. Angle-of-Arrival Estimation in the Presence of Multipath
11(80)
Anastasios Drosopoulos and Simon Haykin
2.1 Introduction
11(2)
2.2 The Low-Angle Tracking Radar Problem
13(1)
2.3 Spectrum Estimation Background
14(4)
2.3.1 The Fundamental Equation of Spectrum Estimation
17(1)
2.4 Thomson's Multi-Taper Method
18(5)
2.4.1 Prolate Spheroidal Wavefunctions and Sequences
19(4)
2.5 Test Dataset and a Comparison of Some Popular Spectrum Estimation Procedures
23(5)
2.5.1 Classical Spectrum Estimation
26(1)
2.5.2 MUSIC and MFBLP
27(1)
2.6 Multi-taper Spectrum Estimation
28(7)
2.6.1 The Adaptive Spectrum
28(4)
2.6.2 The Composite Spectrum
32(1)
2.6.3 Computing the Crude, Adaptive, and Composite Spectra
33(2)
2.7 F-Test for the Line Components
35(25)
2.7.1 Brief Outline of the F-Test
35(2)
2.7.2 The Point Regression Single-Line F-Test
37(2)
2.7.3 The Integral Regression Single-Line F-Test
39(3)
2.7.4 The Point Regression Double-Line F-Test
42(4)
2.7.5 The Integral Regression Double-Line F-Test
46(1)
2.7.6 Line Component Extraction
47(7)
2.7.7 Prewhitening
54(3)
2.7.8 Multiple Snapshots
57(1)
2.7.9 Multiple Snapshot, Single-Line, Point-Regression F-Tests
57(2)
2.7.10 Multiple-Snapshot, Double-Line Point-Regression F-Tests
59(1)
2.8 Experimental Data Description for a Low-Angle Tracking Radar Study
60(3)
2.9 Angle-of-Arrival (AOA) Estimation
63(15)
2.10 Diffuse Multipath Spectrum Estimation
78(7)
2.11 Discussion
85(3)
References
88(3)
3. Time–Frequency Analysis of Sea Clutter
91(28)
David J. Thomson and Simon Haykin
3.1 Introduction
91(1)
3.2 An Overview of Nonstationary Behavior and Time–Frequency Analysis
92(2)
3.3 Theoretical Background on Nonstationarity
94(5)
3.3.1 Multi-taper Estimates
97(1)
3.3.2 Spectrum Estimation as an Inverse Problem
98(1)
3.4 High-Resolution Multi-taper Spectrograms
99(5)
3.4.1 Nonstationary Quadratic-Inverse Theory
101(2)
3.4.2 Multi-taper Estimates of the Loeve Spectrum
103(1)
3.5 Spectrum Analysis of Radar Signals
104(7)
3.6 Discussion
111(2)
3.6.1 Target Detection Rooted in Learning
112(1)
References
113(6)
Part II Dynamic Models
4. Dynamics of Sea Clutter
119(40)
Simon Haykin, Rembrandt Bakker, and Brian Currie
4.1 Introduction
119(4)
4.2 Statistical Nature of Sea Clutter: Classical Approach
123(7)
4.2.1 Background
123(3)
4.2.2 Current Models
126(4)
4.3 Is There a Radar Clutter Attractor?
130(9)
4.3.1 Nonlinear Dynamics
130(2)
4.3.2 Chaotic Invariants
132(1)
4.3.3 Inconclusive Experimental Results on the Chaotic Invariants of Sea Clutter
133(1)
4.3.4 Dynamic Reconstruction
134(3)
4.3.5 Chaos, a Self-Fulfilling Prophecy?
137(2)
4.4 Hybrid AM/FM Model of Sea Clutter
139(11)
4.4.1 Radar Return Plots
139(1)
4.4.2 Rayleigh Fading
139(3)
4.4.3 Time-Doppler Spectra
142(2)
4.4.4 Evidence for Amplitude Modulation, Frequency Modulation, and More
144(2)
4.4.5 Modeling Sea Clutter as a Nonstationary Complex Autoregressive Process
146(4)
4.5 Discussion
150(5)
4.5.1 Nonlinear Dynamics of Sea Clutter
150(1)
4.5.2 Autoregressive Modeling of Sea Clutter
150(1)
4.5.3 State-Space Theory
151(1)
4.5.4 Nonlinear Dynamical Approach Versus Classical Statistical Approach
152(1)
4.5.5 Stochastic Chaos
153(2)
References
155(2)
Appendix A Specifications of the Three Sea-Clutter Sets Used in This Chapter
157(2)
5. Sea-Clutter Nonstationarity: The Influence of Long Waves
159(34)
Maria Greco and Fulvio Gini
5.1 Introduction
159(4)
5.2 Radar and Data Description
163(1)
5.3 Statistical Data Analyses
164(5)
5.4 Modulation of Long Waves: Hybrid AM/FM Model
169(10)
5.5 Nonstationary AR Model
179(2)
5.6 Parametric Analysis of Texture Process
181(7)
5.7 Discussion
188(1)
5.7.1 Autoregressive Modeling of Sea Clutter
189(1)
5.7.2 Cyclostationarity of Sea Clutter
189(1)
References
189(4)
6. Two New Strategies for Target Detection in Sea Clutter
193(28)
Rembrandt Bakker, Brian Currie, and Simon Haykin
6.1 Introduction
193(2)
6.2 Bayesian Direct Filtering Procedure
195(2)
6.2.1 Single-Target Scenario
195(1)
6.2.2 Conditioning on Past and Future Measurements
196(1)
6.3 Operational Details
197(3)
6.3.1 Experimental Data
197(1)
6.3.2 Statistics of Sea Clutter
197(2)
6.3.3 Statistics of Target Returns
199(1)
6.3.4 Motion Model of the Target
200(1)
6.4 Experimental Results on the Bayesian Direct Filter
200(4)
6.5 Additional Notes on the Bayesian Direct Filter
204(1)
6.6 Correlation Anomally Detection Strategy
205(1)
6.7 Experimental Comparison of the Bayesian Direct Filter and Correlation Anomaly Receiver
206(11)
6.7.1 Target-to-Interference Ratio
207(1)
6.7.2 Receiver Comparison
207(10)
6.8 Discussion
217(2)
6.8.1 Further Research
218(1)
References
219(2)
Index 221

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