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Proceedings Paper

Nonlinear processing of radar data for landmine detection
Author(s): Elizabeth E. Bartosz; Keith DeJong; Herbert A. Duvoisin; Geoff Z. Solomon; William J. Steinway; Albert Warren
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Paper Abstract

Outstanding landmine detection has been achieved by the Handheld Standoff Mine Detection System (HSTAMIDS system) in government-run field tests. The use of anomaly detection using principal component analysis (PCA) on the return of ground penetrating radar (GPR) coupled with metal detection is the key to the success of the HSTAMIDS-like system algorithms. Indications of nonlinearities and asymmetries in Humanitarian Demining (HD) data point to modifications to the current PCA algorithm that might prove beneficial. Asymmetries in the distribution of PCA projections of field data have been quantified in Humanitarian Demining (HD) data. An initial correction for the observed asymmetries has improved the False Alarm Rate (FAR) on this data.

Paper Details

Date Published: 21 September 2004
PDF: 4 pages
Proc. SPIE 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX, (21 September 2004); doi: 10.1117/12.544312
Show Author Affiliations
Elizabeth E. Bartosz, CyTerra Corp. (United States)
Keith DeJong, CyTerra Corp. (United States)
Herbert A. Duvoisin, CyTerra Corp. (United States)
Geoff Z. Solomon, CyTerra Corp. (United States)
William J. Steinway, CyTerra Corp. (United States)
Albert Warren, CyTerra Corp. (United States)

Published in SPIE Proceedings Vol. 5415:
Detection and Remediation Technologies for Mines and Minelike Targets IX
Russell S. Harmon; J. Thomas Broach; John H. Holloway Jr., Editor(s)

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