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Proceedings Paper

Anomaly detection of subsurface objects using handheld ground-penetrating radar
Author(s): K. C. Ho; Samuel Harris; Alina Zare; Matthew Cook
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Paper Abstract

This paper develops an anomaly detection algorithm for subsurface object detection using the handheld ground penetrating radar. The algorithm is based on the Mahalanobis distance measure with adaptive update of the background statistics. It processes the data sequentially for each data sample in a causal manner to generate detection confidences. The algorithm is applied to process the data from two different radars, an impulse and a step-frequency, for performance evaluation.

Paper Details

Date Published: 21 May 2015
PDF: 7 pages
Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 94541B (21 May 2015); doi: 10.1117/12.2178584
Show Author Affiliations
K. C. Ho, Univ. of Missouri-Columbia (United States)
Samuel Harris, Univ. of Missouri Columbia (United States)
Alina Zare, Univ. of Missouri-Columbia (United States)
Matthew Cook, Univ. of Missouri-Columbia (United States)

Published in SPIE Proceedings Vol. 9454:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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