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Proceedings Paper

CFAR detection algorithm for acoustic-seismic landmine detection
Author(s): Ghaith M. Matalkah; Mustafa M. Matalgah; James M. Sabatier
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Paper Abstract

Automating the detection process in acoustic-seismic landmine detection speeds up the detection process and eliminates the need for a human operator in the minefield. Previous automatic detection algorithms for acoustic landmine detection showed excellent results for detecting landmines in various environments. However, these algorithms use environment-specific noise-removal procedures that rely on training sets acquired over mine-free areas. In this work, we derive a new detection algorithm that adapts to varying conditions and employs environment-independent techniques. The algorithm is based on the generalized likelihood ratio (GLR) test and asymptotically achieves a constant false alarm rate (CFAR). The algorithm processes the magnitude and phase of the vibrational velocity and shows satisfying results of detecting landmines in gravel and dirt lanes.

Paper Details

Date Published: 4 May 2007
PDF: 9 pages
Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 655303 (4 May 2007); doi: 10.1117/12.719754
Show Author Affiliations
Ghaith M. Matalkah, Univ. of Mississippi (United States)
Mustafa M. Matalgah, Univ. of Mississippi (United States)
James M. Sabatier, Univ. of Mississippi (United States)


Published in SPIE Proceedings Vol. 6553:
Detection and Remediation Technologies for Mines and Minelike Targets XII
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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