Narrow - band processing and fusion approach for explosive hazard detection in

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 full-band 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. Conference Name: Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI Conference Date: 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 full-band 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. Narrow-Band Processing and Fusion Approach for Explosive Hazard Detection in FLGPR Timothy C. Havens* a , James M. Keller a , K.C. Ho a , Tuan T. Ton b , David C. Wong b , and Mehrdad Soumekh c a Dept. of Electrical and Computer Engineering, University of Missouri, Columbia, MO, USA 65211; b U.S. Army REDCOM CERDEC NVESD, Fort Belvoir, Virginia, USA 22060; c Dept. Of Electrical Engineering, University of New York at Buffalo, Amherst, NY, USA 14260