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23 May 2011 Narrow-band processing and fusion approach for explosive hazard detection in FLGPR
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This paper proposes an effective anomaly detection algorithm for a forward-looking ground-penetrating radar(FLGPR). One challenge for threat detection using FLGPR is its high dynamic range in response to different kinds of targets and clutter objects. The application of a fixed threshold for detection in a full-band radar image often yields a large number of false alarms. We propose a method that uses both narrow-band and full-band radar processing, coupled with a classifier that uses complex-valued Gabor filter responses as the features. We then fuse the narrow-band and fullband images into a composite confidence map and detect local maxima in this map to produce candidate alarm locations. Full-band radar images provide a high degree of image resolution, while narrow-band images provide a means to detect targets which have a unique narrow-band signature. Experimental results for our improved detection techniques are demonstrated on data sets collected at a US Army test site.
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Timothy C. Havens, James M. Keller, K. C. Ho, Tuan T. Ton, David C. Wong, and Mehrdad Soumekh "Narrow-band processing and fusion approach for explosive hazard detection in FLGPR", Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 80171F (23 May 2011);

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