Share Email Print

Proceedings Paper

Managing landmine detection sensors: results from application to AMDS data
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Previous work by the authors using information-based sensor management for static target detection has utilized a probability of error performance metric that assumes knowledge of the number of targets present in a grid of cells. Using this probability of error performance metric, target locations are estimated as the N cells with the largest posterior state probabilities of containing a target. In a realistic application, however, the number of targets is not known a priori. The sequential probability ratio test (SPRT) developed by Wald is therefore implemented within the previously developed sensor management framework to allow cell-level decisions of "target" or "no target" to be made based on the observed sensor data. Using these cell-level decisions, more traditional performance metrics such as probability of detection and probability of false alarm may then be calculated for the entire region of interest. The resulting sensor management framework is implemented on a large set of data from the U.S. Army's autonomous mine detection sensors (AMDS) program that has been collected using both ground penetrating radar (GPR) and electromagnetic induction (EMI) sensors. The performance of the sensor manager is compared to two different direct search techniques, and the sensor manager is found to achieve the same Pd performance at a lower cost than either of the direct search techniques. Furthermore, uncertainty in the sensor performance characteristics is also modeled, and the use of uncertainty modeling allows a higher Pd to be obtained than is possible when uncertainty is not modeled within the sensor management framework.

Paper Details

Date Published: 27 April 2007
PDF: 11 pages
Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 65531Y (27 April 2007); doi: 10.1117/12.718457
Show Author Affiliations
Mark P. Kolba, Duke Univ. (United States)
Leslie M. Collins, Duke Univ. (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 Jr., Editor(s)

© SPIE. Terms of Use
Back to Top