ABSTRACT
NonGaussian Clutter ............................................................................. 915
(T. J. Barnard and F. Khan)
15.1.1. Introduction ............................................................................... 915
15.1.2. Background ............................................................................... 916
15.1.3. SIRV Examples ......................................................................... 919
15.1.4. Pareto SIRV GLRT................................................................... 920
15.1.5. Statistical Normalization........................................................... 925
15.1.6. Conclusion................................................................................. 927
15.2. NonGaussian Clutter Modeling and Application to
Radar Target Detection ......................................................................... 928
(A. D. Keckler, D. L. Stadelman, and D. D. Weiner)
15.2.1. Introduction ............................................................................... 928
15.2.2. Summary of the SIRV Model ................................................... 929
15.2.3. Distribution Approximation Using the Ozturk Algorithm....... 930
15.2.4. Approximation of SIRVs .......................................................... 933
15.2.5. NonGaussian Receiver Performance ........................................ 936
15.2.6. Concluding Remarks ................................................................. 938
15.3. Adaptive Ozturk-Based Receivers for Small
Signal Detection in Impulsive NonGaussian Clutter............................ 938
(D. L. Stadelman, A. D. Keckler, and D. D. Weiner)
15.3.1. Introduction ............................................................................... 938
15.3.2. Summary of the SIRV Model ................................................... 940
15.3.3. The Ozturk Algorithm and SIRV PDF Approximation ........... 941
15.3.4. NonGaussian SIRV Receivers .................................................. 944
15.3.5. Graphical Representation of SIRV Receiver Behavior............ 945
15.3.6. Adaptive Ozturk-Based Receiver ............................................. 951
15.3.7. Conclusions ............................................................................... 953
15.4. Efficient Determination of Thresholds via Importance Sampling
for Monte Carlo Evaluation of Radar Performance in
NonGaussian Clutter ............................................................................. 955
(D. L. Stadelman, D. D. Weiner, and A. D. Keckler)
15.4.1. Introduction ............................................................................... 955
15.4.2. The Complex SIRV Clutter Model........................................... 956
15.4.3.1. Known Covariance Matrix Case................................ 959
15.4.3.2. Unknown Covariance Matrix Case............................ 959
15.4.4. Importance Sampling ................................................................ 960
15.4.5. Estimation of SIRV Detector Thresholds
with Importance Sampling........................................................ 962
15.4.6. Extreme Value Theory Approximation .................................... 967
15.5. Rejection-Method Bounds for Monte Carlo Simulation of SIRVs ...... 968
(A. D. Keckler and D. D. Weiner)
15.5.1. Introduction ............................................................................... 968
15.5.2. Summary of the SIRV Model ................................................... 969
15.5.3. Generation of SIRV Distributed Samples ................................ 970
15.5.4. Generation of PDF Bounds....................................................... 975
15.5.5. Concluding Remarks ................................................................. 979
15.6. Optimal NonGaussian Processing in Spherically
Invariant Interference ............................................................................ 980
(D. Stadelman and D. D. Weiner)
15.6.1. Introduction ............................................................................... 980
15.6.2. A Review of the SIRV Model .................................................. 982
15.6.2.1. Definition of the SIRV Model ................................... 982
15.6.2.2. SIRV Properties ......................................................... 984
15.6.2.3. The Complex SIRV Model ........................................ 987
15.6.2.4. Examples .................................................................... 988
15.6.3. Optimal Detection in NonGaussian SIRV Clutter ................... 988
15.6.3.1. Introduction ................................................................ 988
15.6.3.2. Completely Known Signals ....................................... 989
15.6.3.3. Signals with Random Parameters .............................. 990
15.6.3.4. Generalized Likelihood Ratio Test.......................... 1005
15.6.3.5. Maximum Likelihood Matched Filter ..................... 1008
15.6.4. Nonlinear Receiver Performance............................................ 1011
15.6.4.1. Introduction .............................................................. 1011
15.6.4.2. Indirect Simulation of SIRV Receiver Statistics..... 1012
15.6.4.3. Student t SIRV Results ............................................ 1014
15.6.4.4. DGM Results............................................................ 1018
15.6.4.5. NP vs. GLRT Receiver Comparison ....................... 1020
15.6.4.6. Additional Implementation Issues ........................... 1022
15.6.4.7. Summary .................................................................. 1023
15.7. Multichannel Detection for Correlated NonGaussian
Random Processes Based on Innovations........................................... 1024
(M. Rangaswamy, J. H. Michels, and D. D. Weiner)
15.7.1. Introduction ............................................................................. 1024
15.7.2. Preliminaries............................................................................ 1025
15.7.3. Minimum Mean-Square Estimation Involving SIRPs............ 1026
15.7.4. Innovations-Based Detection Algorithm
Likelihood Ratio ...................................................... 1028
15.7.4.2. Sequential Form of the Multichannel
Likelihood Ratio ...................................................... 1029
15.7.5. Detection Results Using Monte-Carlo Simulation ................. 1032
15.7.6. Estimator Performance for SIRPs........................................... 1036
15.7.7. Conclusion............................................................................... 1037
Three critical requirements of active sonar systems are as follows:
(1) constant false-alarm rate (CFAR) relative to undesired clutter;
(2) maximized probability of detection (PD) relative to desired contacts;
(3) uniform background on the display.
