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Proceedings Paper

Real-time adaptable subspace method for automatic mine detection
Author(s): Ssu-Hsin Yu; Avinash Gandhe; Thomas R. Witten; Raman K. Mehra
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Paper Abstract

A major difficulty in automatic mine detection arises from the fact that the physical properties of background soil can vary significantly from one location to another. This in turns alters the sensor signals of the buried mines. Hence, a robust ATR algorithm for mine detection requires that the algorithm be adaptable to environmental changes. Moreover, mine features used for detection should be invariant to background variation. We have developed an ATR algorithm that uses only background soil data during the training phase and mine features that are less affected by soil changes. Since the algorithm uses only the background data for training, not only is it much easier to tailor the algorithm to a minefield but the algorithm can also be adapted in real-time during operation. This further improves robustness of the process. The algorithm demonstrated good performance when tested on ground penetrating radar data acquired from U.S. Army test lanes.

Paper Details

Date Published: 13 August 2002
PDF: 10 pages
Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); doi: 10.1117/12.479071
Show Author Affiliations
Ssu-Hsin Yu, Scientific Systems Co., Inc. (United States)
Avinash Gandhe, Scientific Systems Co., Inc. (United States)
Thomas R. Witten, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)

Published in SPIE Proceedings Vol. 4742:
Detection and Remediation Technologies for Mines and Minelike Targets VII
J. Thomas Broach; Russell S Harmon; Gerald J. Dobeck, Editor(s)

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