Emitter Detection and Geolocation for Electronic Warfare (The Artech House Electronic Warfare Library)

This comprehensive resource provides theoretical formulation for detecting and geolocating non-cooperative emitters. Implementation of geolocation algorithms are discussed, as well as performance prediction of a hypothetical passive location system for systems analysis or vulnerability calculation. Comparison of novel direction finding and geolocation algorithms to classical forms are also included. Rooted in statistical signal processing and array processing theory, this book also provides an overview of the application of novel detection and estimation algorithms to real world problems in EW. The book is divided into three parts: detection, angle of arrival estimation, and geolocation. Each section begins with an introductory chapter covering the relevant signal processing theory (either detection or estimation), then provides a series of chapters covering specific methods to achieve the desired end-product. MATLAB(R) code is provided to assist readers with relevant probability and statistics, RF propagation, atmospheric absorption, and noise, giving readers an understanding of the implementation of the algorithms in the book, as well as developing new approaches to solving problems. Packed with problem sets and examples, this book strikes a balance between introductory texts and reference manuals, making it useful for novice as well as advanced practitioners. Contents Preface Chapter 1 Introduction 1.1 Detection Of Threat Emitters 1.2 Angle Of Arrival (aoa) Estimation 1.3 Geolocation Of Threat Emitters 1.3.1 Geolocation By Satellite 1.4 Signals Of Interest 1.5 Nonmilitary Uses 1.6 Limitations References I Detection of Threat Emitters Chapter 2 Detection Theory 2.1 Background 2.1.1 Sources Of Variation 2.1.2 Likelihood Function 2.1.3 Sufficient Statistic Example 2.1 Sample Mean 2.2 Binary Hypothesis Testing Example 2.2 Gaussian Random Vector 2.3 Composite Hypothesis 2.4 Constant False-alarm Rate Detectors 2.4.1 Side Channel Information 2.5 Problem Set References Chapter 3 Detection of CW Signals 3.1 Background 3.2 Formulation 3.3 Solution 3.3.1 Threshold Selection 3.3.2 Detection Algorithm 3.3.3 Detection Performance 3.4 Performance Analysis 3.4.1 Brief Review Of Rf Propagation 3.4.2 Detection Of An Fm Broadcast Tower Example 3.1 Maximum Detection Range Of An Fm Radio Station 3.4.3 Cw Radar Detection Example 3.2 Maximum Detection Range Of A Cw Radar 3.5 Problem Set References Chapter 4 Detection of Spread Spectrum Signals 4.1 Background 4.2 Formulation 4.2.1 Dsss Encoding 4.2.2 Spread Spectrum Radar Signals 4.3 Solution 4.3.1 Energy Detectors 4.3.2 Cyclostationary Detectors 4.3.3 Cross-correlation Detectors 4.4 Performance Analysis 4.4.1 Detection Of A 3g Cdma Cell Signal Example 4.1 Maximum Detection Range Of A 3g Cdma Signal 4.4.2 Detection Of Awideband Radar Pulse Example 4.2 Maximum Detection Range Of An Lpi Radar Pulse 4.5 Limitations 4.6 Problem Set References Chapter 5 Scanning Receivers 5.1 Digital Receivers 5.1.1 In-phase (i) And Quadrature (q) Digitization 5.2 If Receivers Example 5.1 Frequency Hopping Signal Detection 5.3 Frequency Resolution Example 5.2 Fmcw Radar Example 5.3 Pulsed Frequency Agile Radar 5.4 Problem Set References Chapter 6 Estimation Theory 6.1 Background 6.2 Maximum Likelihood Estimation Example 6.1 Sample Mean And Sample Variance 6.3 Other Estimators 6.3.1 Minimum Variance Unbiased Estimators 6.3.2 Bayes Estimators Example 6.2 Bayes Estimation Example Example 6.3 Bayes Estimation With Informative Prior 6.3.3 Least Square Estimators 6.3.4 Convex Estimators 6.3.5 Tracking Estimators 6.4 Performance Measures 6.4.1 Root Mean Squared Error (rmse) 6.4.2 Crlb Example 6.4 Crlb Of Gaussian With Unknown Mean Example 6.5 Deriving An Efficient Estimator 6.4.3 Angle Error Variance And Confidence Intervals Example 6.6 Aoa Accuracy 6.5 Problem Set References II Angle of Arrival Estimation Chapter 7 Direction-Finding Systems 7.1 Beam Pattern-based Direction Finding 7.1.1 Implementation 7.1.2 Performance 7.2 Watson-watt Direction Finding 7.2.1 Implementation 7.2.2 Performance 7.3 Doppler-based Direction Finding 7.3.1 Formulation 7.3.2 Implementation 7.3.3 Performance 7.4 Phase Interferometry 7.4.1 Implementation 7.4.2 Performance 7.4.3 Resolving Ambiguities With Multiple Baselines 7.5 Performance Comparison Example 7.1 Direction Finding With An Adcock Antenna Example 7.2 Watson-watt Direction Finding Example 7.3 Doppler-based Direction Finding Example Example 7.4 Interferometer Df Example 7.6 Monopulse Direction Finding 7.6.1 Performance 7.7 Problem Set References Chapter 8 Array-Based AOA 8.1 Background 8.1.1 Nonstandard Array Configurations 8.2 Formulation 8.2.1 Multiple Planewaves 8.2.2 Wideband Signals 8.2.3 Array Beamforming 8.2.4 Nonisotropic Element Patterns 8.2.5 Gain And Beamwidth 8.2.6 Array Tapers 8.2.7 Two-dimensional Arrays 8.3 Solution 8.3.1 Signal Models 8.3.2 Maximum Likelihood Estimation 8.3.3 Beamformer Scanning Example 8.1 Vhf Push-to-talk Radio Df 8.3.4 Subspace-based Methods 8.4 Performance Analysis 8.4.1 Gaussian Signal Model 8.4.2 Deterministic Signal Model Example 8.2 Airborne Datalink Df 8.5 Problem Set References III Geolocation of Threat Emitters Chapter 9 Geolocation of Emitters 9.1 Background 9.2 Performance Metrics 9.2.1 Error Ellipse Example 9.1 Computing The Error Ellipse 9.2.2 Cep Example 9.2 Compute The Cep 9.2.3 Matlab Code 9.3 Crlb 9.4 Trackers 9.5 Geolocation Algorithms 9.5.1 Ongoing Research 9.6 Problem Set References Chapter 10 Triangulation of AOA Measurements 10.1 Background 10.2 Formulation 10.2.1 3-d Geometry 10.3 Solution 10.3.1 Geometric Solution For Two Measurements 10.3.2 Geometric Solutions For Three Or More Measurements 10.3.3 Maximum Likelihood Estimate 10.3.4 Iterative Least Squares 10.3.5 Gradient Descent Example 10.1 Aoa Triangulation 10.4 Other Solutions 10.5 Performance Analysis Example 10.2 Two-sensor Df System Performance Example 10.3 Multibaseline Aoa Performance 10.6 Problem Set References Chapter 11 TDOA 11.1 Background 11.2 Formulation 11.2.1 Isochrones 11.2.2 Number Of Sensors 11.3 Solution 11.3.1 Maximum Likelihood Estimate 11.3.2 Iterative Least Squares Solution 11.3.3 Gradient Descent Algorithms 11.3.4 Chan-ho Approach 11.3.5 Spherical Methods 11.4 Tdoa Estimation 11.4.1 Time Of Arrival Detection 11.4.2 Cross-correlation Processing 11.4.3 Clock Synchronization 11.5 Geolocation Performance Example 11.1 Four-channel Tdoa Solution 11.6 Limitations 11.7 Problem Set References Chapter 12 FDOA 12.1 Background 12.2 Formulation 12.3 Solution 12.3.1 Maximum Likelihood Estimate 12.3.2 Iterative Least Squares Solution 12.3.3 Gradient Descent Algorithms 12.3.4 Other Approaches 12.4 Fdoa Estimation 12.4.1 Frequency Of Arrival Estimation 12.4.2 Fdoa Estimation 12.4.3 Limitations Of Frequency Estimation 12.5 Geolocation Performance Example 12.1 Four-channel Fdoa Solution 12.6 Limitations 12.7 Problem Set References Chapter 13 Hybrid TDOA/FDOA 13.1 Background 13.2 Formulation 13.3 Solution 13.3.1 Numerically Tractable Solutions Example 13.1 Three-channel Hybrid Solution Example 13.2 Heterogeneous Sensors 13.3.2 Other Solutions 13.4 Joint Parameter Estimation 13.4.1 Aoa Estimation 13.4.2 Joint Estimation Of Time/frequency Difference 13.4.3 Full Covariance Matrix 13.5 Performance Analysis 13.6 Limitations 13.7 Problem Set References Appendix A Probability and Statistics A.1 Common Distributions A.1.1 Gaussian Random Variable A.1.2 Complex Gaussian Random Variable A.1.3 Chi-squared Random Variable A.1.4 Noncentral Chi-squared Random Variable A.1.5 Rayleigh Random Variable A.1.6 Rician Random Variable A.2 Student’s T Distribution A.3 Random Vectors A.3.1 Gaussian Random Vectors A.3.2 Complex Gaussian Random Vectors References Appendix B RF Propagation B.1 Free-space Propagation B.2 Two-ray Propagation B.3 Fresnel Zone B.4 Knife-edge Diffraction B.5 Other Models B.6 Urban Signal Propagation References Appendix C Atmospheric Absorption C.1 Losses Due To Absorption By Gases C.2 Losses Due To Absorption By Rain C.3 Losses Due To Absorption By Clouds And Fog C.4 Standard Atmosphere C.5 Wrapper Function C.6 Zenith Attenuation C.7 Matlab Toolboxes And Model Fidelity References Appendix D System Noise D.1 Additive White Gaussian Noise D.2 Colored Noise D.3 Sky Noise D.3.1 Cosmic Noise D.3.2 Atmospheric Noise D.3.3 Ground Noise D.4 Urban (man-made) Noise References About the Author Index PART XVII Appendix A PART XVIII Appendix B PART XIX Appendix C PART XX Appendix D