Multi-band sensor-fused explosive hazards detection in forward-looking ground penetrating radar

Document Type

Conference Proceeding

Publication Date

1-1-2014

Abstract

Explosive hazard detection and remediation is a pertinent area of interest for the U.S. Army. There are many types of detection methods that the Army has or is currently investigating, including ground-penetrating radar, thermal and visible spectrum cameras, acoustic arrays, laser vibrometers, etc. Since standoff range is an important characteristic for sensor performance, forward-looking ground-penetrating radar has been investigated for some time. Recently, the Army has begun testing a forward-looking system that combines L-band and X-band radar arrays. Our work focuses on developing imaging and detection methods for this sensor-fused system. In this paper, we investigate approaches that fuse L-band radar and X-band radar for explosive hazard detection and false alarm rejection. We use multiple kernel learning with support vector machines as the classification method and histogram of gradients (HOG) and local statistics as the main feature descriptors. We also perform preliminary testing on a context aware approach for detection. Results on government furnished data show that our false alarm rejection method improves area-under-ROC by up to 158%. © 2014 SPIE.

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

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