Managing landmine detection sensors: results from application to AMDS data

Mark P. Kolba; Leslie M. Collins

doi:10.1117/12.718457

27 April 2007 Managing landmine detection sensors: results from application to AMDS data

Mark P. Kolba, Leslie M. Collins

Proceedings Volume 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII; 65531Y (2007) https://doi.org/10.1117/12.718457
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

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 P_d 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 P_d to be obtained than is possible when uncertainty is not modeled within the sensor management framework.

Citation Download Citation

Mark P. Kolba and Leslie M. Collins "Managing landmine detection sensors: results from application to AMDS data", Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 65531Y (27 April 2007); https://doi.org/10.1117/12.718457

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available