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E-raamat: Practical Geolocation for Electronic Warfare Using MATLAB

  • Formaat: 220 pages
  • Ilmumisaeg: 31-Jan-2022
  • Kirjastus: Artech House Publishers
  • ISBN-13: 9781630818890
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  • Formaat: 220 pages
  • Ilmumisaeg: 31-Jan-2022
  • Kirjastus: Artech House Publishers
  • ISBN-13: 9781630818890
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This text explores the practical realities that arise from the employment of geolocation for electronic warfare in real-world systems, including position of the target, errors in sensor position, orientation, or velocity, and the impact of repeated measurements over time. The problems solved in the book have direct relevance to accurately locating and tracking UAVs, planes, and ships.

 

As a companion volume to the authors previous book Emitter Detection and Geolocation for Electronic Warfare (Artech House, 2019), this book goes in depth on real-world complications that include: working within and converting between different coordinate systems, incorporation of prior information about targets, sensor uncertainties, the use of multiple snapshots over time, and estimating the current position and velocity of moving targets. The e-book version described here includes several links to software and videos that can be downloaded from the publicly available Git repository. The book also includes all MATLAB code necessary to develop novel algorithms that allow comparisons to classical techniques and enable you to account for errors in timing, position, velocity, or orientation of the sensors.

 

With its unique and updated coverage of detailed geolocation techniques and data, and easy linkable access to additional software and videos, this is a must-have book for engineers and electronic warfare practitioners who need the best information available on the development or employment of geolocation algorithms. It is also a useful teaching resource for faculty and students in engineering departments covering RF signal processing topics, as well as anyone interested in novel applications of SDRs and UAVs.
Preface xi
Chapter 1 Introduction
1(12)
1.1 Receiver Processing
1(1)
1.2 Geolocation
2(7)
1.2.1 Practical Considerations of Geolocation
3(6)
1.3 Associated Software
9(4)
1.3.1 MATLAB®
9(1)
1.3.2 Textbook Software
10(1)
1.3.3 Python Software
10(1)
References
10(3)
Chapter 2 Review of Emitter Geolocation
13(32)
2.1 Geolocation Measurements and Their Likelihood Functions
13(12)
2.1.1 Likelihood Function for AOA Measurements
14(2)
2.1.2 Likelihood Function for TDOA Measurements
16(1)
2.1.3 Likelihood Function for FDOA Measurements
17(2)
2.1.4 Likelihood Function for Hybrid Measurements
19(1)
2.1.5 Generating Measurements and Likelihood Functions
20(5)
2.2 Estimators
25(6)
2.2.1 Maximum Likelihood Estimation
25(1)
2.2.2 Maximum a Posterior Optimization
26(1)
2.2.3 Convex Optimization
26(1)
2.2.4 Least Square Estimators
27(1)
2.2.5 Using Estimators for Geolocation
28(3)
2.3 Other Geolocation Algorithms
31(1)
2.4 Performance Measures
31(8)
2.4.1 Root Mean Squared Error (RMSE)
31(1)
2.4.2 Error Ellipse
32(1)
2.4.3 Circular Error Probable (CEP)
32(1)
2.4.4 Statistical Bounds
33(3)
2.4.5 Statistical Bounds for Common Geolocation Data
36(2)
2.4.6 Calculating CRLB for Geolocation Measurements
38(1)
2.5 Discussion
39(2)
2.6 Problem Set
41(4)
References
41(4)
Chapter 3 Sensor Selection
45(26)
3.1 Introduction
45(2)
3.2 Measurement Sets
47(2)
3.2.1 Full Measurement Set
47(1)
3.2.2 Nonredundant Set
48(1)
3.3 Measurement Statistics of Sensor Pairs
49(8)
3.3.1 Sensor Pair Cross-Covariance
50(1)
3.3.2 Usage
51(3)
3.3.3 Generating Measurements
54(2)
3.3.4 Jacobian Matrix of Arbitrary Sensor Pairs
56(1)
3.4 Performance Analysis
57(9)
3.5 Problem Set
66(5)
References
67(4)
Chapter 4 Coordinate Systems
71(24)
4.1 Local Coordinate Systems
71(4)
4.1.1 Cartesian Coordinates
71(2)
4.1.2 Spherical Coordinates
73(2)
4.2 Global Coordinate Systems
75(6)
4.2.1 Models of the Earth
75(4)
4.2.2 Latitude and Longitude
79(1)
4.2.3 Earth-Centered Earth-Fixed (ECEF)
80(1)
4.2.4 Earth-Centered Inertial (ECI)
80(1)
4.3 Usage
81(10)
4.3.1 Conversion between ECEF and LLA
82(1)
4.3.2 Conversion between ENU and ECEF
83(2)
4.3.3 ENU Adapted for Spherical Earth
85(1)
4.3.4 Examples
86(5)
4.4 Problem Set
91(4)
References
93(2)
Chapter 5 Geolocation with Target Constraints
95(34)
5.1 Geolocation with Known Target Altitude
96(17)
5.1.1 Optimization Problem Formulation
96(2)
5.1.2 Solvers
98(9)
5.1.3 Performance Analysis
107(6)
5.2 Geolocation with Known Altitude Bounds
113(6)
5.2.1 Optimization Problem Formulation
113(1)
5.2.2 Solvers
114(5)
5.2.3 Performance Analysis
119(1)
5.3 Geolocation with Statistical Priors
119(7)
5.3.1 Example Priors
121(1)
5.3.2 Solving Geolocation with Priors
121(3)
5.3.3 Performance Analysis
124(2)
5.4 Problem Set
126(3)
References
127(2)
Chapter 6 Geolocation with Sensor Uncertainties
129(40)
6.1 Formulation
129(16)
6.1.1 Gradient of the Measurement Function with Sensor Uncertainties
134(6)
6.1.2 Sensor Position Covariance
140(5)
6.2 Approach
145(11)
6.2.1 Required Observations
146(2)
6.2.2 Maximum Likelihood
148(5)
6.2.3 Iterative Solvers
153(3)
6.3 Calibration Emitters
156(6)
6.3.1 Measurement Bias Estimation
157(2)
6.3.2 Sensor Position Error Estimation
159(1)
6.3.3 Estimating Target Position
159(3)
6.4 Other Solution Approaches
162(2)
6.5 Performance Analysis
164(1)
6.6 Problem Set
164(5)
References
165(4)
Chapter 7 Geolocation with Multiple Snapshots
169(26)
7.1 Convergence of Multiple Measurements
169(15)
7.1.1 Measurement Space Solutions
174(4)
7.1.2 State Space Solutions
178(6)
7.2 Geolocation of a Stationary Target from Moving Sensors
184(8)
7.2.1 Measurement Space Solutions
184(1)
7.2.2 State Space Solutions
185(3)
7.2.3 Complex Scenarios
188(1)
7.2.4 Degenerate Geometries
188(4)
7.3 Conclusion
192(1)
7.4 Problem Set
192(3)
References
192(3)
Chapter 8 Geolocation of Moving Targets
195(28)
8.1 Introduction
195(1)
8.2 An Introduction to Tracking
195(5)
8.2.1 Update Stage
196(2)
8.2.2 Prediction Stage
198(1)
8.2.3 Limitations
199(1)
8.2.4 Coordinate Selection
199(1)
8.3 State Space Models
200(14)
8.3.1 State Space Representation of Targets
200(1)
8.3.2 Kinematic Models
200(3)
8.3.3 Process Noise
203(1)
8.3.4 Measurement Models
204(10)
8.4 Advanced Tracking Concepts
214(4)
8.5 Problem Set
218(5)
References
218(5)
Appendix A Derivation of the Fisher Information Matrix for Phase, Delay, and Doppler Estimation
223(4)
References
225(2)
About the Author 227(2)
Index 229