Statistical processing of ground-penetrating radar signals for mine detection

Brian M. Duston; David A. Lang

doi:10.1117/12.445502

18 October 2001 Statistical processing of ground-penetrating radar signals for mine detection

Brian M. Duston, David A. Lang

Proceedings Volume 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI; (2001) https://doi.org/10.1117/12.445502
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

The Mine Hunter/Killer Close-In Detector (MH/K CID) uses Ground Penetrating Radar (GPR) as it's primary sensor. The GPR processor requires a sensitive detection algorithm to detect anomalies that may indicate the presence of a buried land mine. A general formula for a statistical detector is presented, consisting of a median filter to eliminate outliers, a local mean estimator using a Blackman window and a local covariance estimator. Advanced methods for robust estimation of the covariance matrix are presented and evaluated using data collected by the CID over buried land mines. This GPR detector is used as a preprocessor for image processing and mine classification algorithms that are used by a sensor fusion processor to determine when to activate the 'Killer' mechanism to neutralize the buried mine.

Citation Download Citation

Brian M. Duston and David A. Lang "Statistical processing of ground-penetrating radar signals for mine detection", Proc. SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, (18 October 2001); https://doi.org/10.1117/12.445502

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