Sensors 2013, 13(1), 1151-1157; doi:10.3390/s130101151

New Book Received *
Electronic Warfare Target Location Methods, Second Edition. Edited by Richard A. Poisel, Artech House, 2012; 422 pages. Price: £99.00, ISBN 978-1-60807-523-2
Shu-Kun Lin
MDPI AG, Kandererstrasse 25, CH-4057 Basel, Switzerland; E-Mail: lin@mdpi.com
Received: 10 January 2013 / Accepted: 14 January 2013 / Published: 17 January 2013

The following paragraphs are reproduced from the website of the publisher [1].

Describing the mathematical development underlying current and classical methods of geolocating electronic systems that are emitting, this newly revised and greatly expanded edition of a classic Artech House book offers practical guidance in electronic warfare target location. The Second Edition features a wealth of additional material including new chapters on time delay estimation, direction finding techniques, and the MUSIC algorithm. This practical resource provides you with critical design information on geolocation algorithms, and establishes the fundamentals of existing algorithms as a launch point for further algorithm development. You gain an in-depth understanding of key target location methods that you can effectively apply to your work in the field. You discover triangulation algorithms that offer a highly efficient way to geolocate targets when the real estate on the sensor systems is adequate to support an antenna array. The book also presents quadratic geolocation techniques that can be implemented with extremely modest antennas—frequently a single dipole or monopole. Moreover, this authoritative volume details methods for geolocating the source of high frequency signals with a single sensor site.

Table of Contents
Preface xv
Chapter 1 Introduction to Emitter Geolocation
1.1Introduction
1.2Gradient Descent Algorithm
1.3Concluding Remarks
References
Chapter 2 Triangulation
2.1Introduction
2.2Basic Concepts
2.3Least-Squares Error Estimation
2.4Total Least-Squares Estimation
2.5Least-Squares Distance Error PF Algorithm
2.5.1Brown's Least-Squares Triangulation Algorithm
2.5.2Hemispheric Least-Squares Error Estimation Algorithm
2.5.3Pages-Zamora Least-Squares
2.5.4Total Least-Squares Error
2.6Minimum Mean-Squares Error Estimation
2.6.1Dynamical Systems
2.6.2Linear Minimum Mean-Squares Estimation
2.6.3Target Location Estimation with the Linear Model
2.6.4Kalman Filter Methods
2.7The Discrete Probability Density Method
2.8Generalized Bearings
2.9Maximum Likelihood PF Algorithm
2.9.1Maximum Likelihood Estimation Triangulation Algorithm
2.9.2Maximum Likelihood Estimation Algorithm Comparison
2.10Multiple Sample Correlation
2.11Bearing-Only Target Motion Analysis
2.12Sources of Error in Triangulation
2.12.1Geometric Dilution of Precision in Triangulation
2.12.2LOB Error
2.12.3Effects of Bias on Bearing-Only PF
2.12.4Combining Noisy LOB Measurements
2.12.5Effects of Navigation Error
2.13Concluding Remarks
References
Appendix 2A Least-Squares Error Estimation Program Listing
Appendix 2B Generalized Bearing Program Listing
Chapter 3 DF Techniques
3.1Introduction
3.2Array Processing Direction of Arrival Measurement Methods
3.2.1Introduction
3.2.2The Model
3.2.3Array Covariance Modeling
3.2.4Direction of Arrival
3.2.5Subspace-Based Methods
3.2.6Beamforming AOA Estimation
3.2.7Maximum Likelihood AOA Estimation
3.2.8Least-Square Error AOA Estimation
3.2.9Decoupling Sample Source Signals from AOA Parameters
3.2.10Gram-Schmidt Orthogonalization
3.2.11Nonlinear Programming
3.3Other Methods of Estimating the AOA
3.3.1Phase Interferometry
3.3.2Amplitude Systems
3.3.3Doppler Direction Finder
3.4MSE Phase Interferometer
3.4.1Introduction
3.4.2The Algorithm
3.4.3Simulation
3.5DF with a Butler Matrix
3.5.1Introduction
3.5.2Beamforming Network
3.5.3Summary
3.6Phase Difference Estimation Using SAW Devices
3.6.1Introduction
3.6.2SAW Characteristics
3.7Concluding Remarks
References
Chapter 4 MUSIC
4.1Introduction
4.2MUSIC Overview
4.3MUSIC
4.3.1The MUSIC Algorithm
4.4Performance of MUSIC in the Presence of Modeling Errors
4.4.1Model Errors
4.4.2Error Expressions
4.4.3Results
4.5Determining the Number of Wavefields
4.6Effect of Phase Errors on the Accuracy of MUSIC
4.6.1Introduction
4.6.2Accuracy
4.6.3Solutions for Errors
4.6.4Statistics
4.6.5Horizontal Planar Arrays
4.6.6Simulations
4.6.7Summary
4.7Other Superresolution Algorithms
4.7.1Maximum Likelihood Method
4.7.2Adaptive Angular Response
4.7.3Thermal Noise Algorithm
4.7.4Maximum Entropy Method
4.7.5Comparisons
4.8Concluding Remarks
References
Chapter 5 Quadratic Position-Fixing Methods
5.1Introduction
5.2TDOA Position-Fixing Techniques
5.2.1Introduction
5.2.2TDOA
5.2.3Calculating the PF with TDOAs
5.2.4Nonlinear Least-Squares
5.2.5TDOA Measurement Accuracy
5.2.6TDOA PFs with Noisy Measurements
5.2.7TDOA Dilution of Precision
5.2.8Bias Effects of TDOA PF Estimation
5.2.9Effects of Movement on TDOA PF Estimation
5.3Differential Doppler
5.3.1Introduction
5.3.2DD
5.3.3DD Measurement Accuracy
5.3.4Maximum Likelihood DD Algorithms
5.3.5Cross-Ambiguity Function
5.3.6Estimating the DD of a Sinusoid in Noise Using Phase Data
5.3.7Effects of Motion on DD PF Estimating
5.4Range Difference Methods
5.4.1Introduction
5.4.2Least-Squared Range Difference Methods
5.4.3Range Difference Using Feasible Bivectors
5.5Concluding Remarks
References
Chapter 6 Time Delay Estimation
6.1Introduction
6.2System Overview
6.3Cross Correlation
6.3.1Error Analysis of the Cross-Correlation Method
6.3.2Flat Noise Spectra: Arbitrary Signal Spectrum
6.3.3Flat Noise Spectra: Flat Signal Spectrum
6.4Generalized Cross-Correlation
6.5Estimating the Time Delay with the Generalized Correlation Method
6.5.1Roth Process
6.5.2Smoothed Coherence Transform (SCOT)
6.5.3Phase Transform (PHAT)
6.5.4Eckart Filter
6.5.5Maximum Likelihood
6.5.6Variance of the Delay Estimators
6.6Time Delay Estimation Using the Phase of the Cross-Spectral Density
6.6.1Introduction
6.6.2Data Model
6.6.3Properties of the Sample CSD
6.6.4TDOA Estimation
6.6.5Cramer-Rao Bound
6.6.6Other Considerations
6.6.7Summary
6.7Effects of Frequency and Phase Errors in EW TDOA Direction-Finding Systems
6.7.1Introduction
6.7.2Perfect Synchronization
6.7.3Errors in Synchronization
6.7.4Effects of Finite Sample Time
6.7.5White Noise Signal
6.7.6Simulation Results
6.7.7Estimator Performance
6.7.8Ramifications
6.7.9Summary
6.8Concluding Remarks
References
Chapter 7 Single-Site Location Techniques
7.1Introduction
7.2HF Signal Propagation
7.2.1Ionograms
7.2.2Magnetic Field Effects
7.3Single-Site Location
7.4Passive SSL
7.5Determining the Reflection Delay with the Cepstrum
7.6MUSIC Cepstrum SSL
7.7Earth Curvature
7.8Skywave DF Errors
7.8.1Introduction
7.8.2Magnetic Field Effects
7.8.3Ross Curve
7.8.4Bailey Curve
7.9Ray Tracing
7.9.1Parabolic Modeling
7.10Accuracy Comparison of SSL and Triangulation for Ionospherically Propagated Signals
7.10.1Introduction
7.10.2Spherical Model
7.10.3Plane Model
7.10.4Comparison Between SSL and Triangulation
7.10.5Summary
7.11Concluding Remarks
References
Appendix A Grassmann Algebra
A.1Background
A.2Introduction
A.3Exterior Product
A.3.1Properties of the Exterior Product
A.3.2m-Vectors
A.4Regressive Product
A.4.1Unions and Intersections of Spaces
A.4.2Properties of the Regressive Product
A.4.3The Common Factor Axiom
A.4.4The Common Factor Theorem
A.4.5The Intersection of Two Bivectors in a 3-D Space
A.5Geometric Interpretations
A.5.1Points and Vectors
A.5.2Sums and Differences of Points
A.5.3Lines and Planes
A.5.4Intersection of Two Lines
A.6The Complement
A.6.1The Complement as a Correspondence Between Spaces
A.6.2The Euclidean Complement
A.6.3The Complement of a Complement
A.6.4The Complement Axiom
A.7The Interior Product
A.7.1Inner Products and Scalar Products
A.7.2Calculating Interior Products
A.7.3Expanding Interior Products
A.7.4The Interior Product of a Bivector and a Vector
A.8Concluding Remarks
References
Appendix B Nonlinear Programming Algorithms
B.1Introduction
B.2Steepest Descent
B.2.1Introduction
B.2.2Method of Steepest Descent
B.2.3Convergence
B.2.4Scaling
B.2.5Extensions
B.3Gauss-Newton Method
B.4Levenberg-Marquardt Algorithm
B.4.1Introduction
B.4.2Nonlinear Least-Squares Minimization
B.4.3LM as a Blend of Gradient Descent and Gauss-Newton Iteration
B.5Concluding Remarks
References
Acronyms
Symbols
About the Author
Index

Note

  1. The website for this book is: http://www.artechhouse.com/International/Books/Introduction-to-Modern-EW-Systems-1958.aspx
  • *Editor's Note: The brief summary and the contents of the books are reported as provided by the authors or the publishers. Authors and publishers are encouraged to send review copies of their recent books of potential interest to readers of Sensors to the Publisher (Dr. Shu-Kun Lin, Multidisciplinary Digital Publishing Institute (MDPI), Kandererstrasse 25, CH-4057 Basel, Switzerland. Tel. +41-61-683-77-34; Fax: +41-61-302-89-18; E-Mail: lin@mdpi.com). Some books will be offered to the scholarly community for the purpose of preparing full-length reviews.
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