Share Email Print
cover

Proceedings Paper

Sequential feature selection for detecting buried objects using forward looking ground penetrating radar
Author(s): Darren Shaw; Kevin Stone; K. C. Ho; James M. Keller; Robert H. Luke; Brian P. Burns
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Forward looking ground penetrating radar (FLGPR) has the benefit of detecting objects at a significant standoff distance. The FLGPR signal is radiated over a large surface area and the radar signal return is often weak. Improving detection, especially for buried in road targets, while maintaining an acceptable false alarm rate remains to be a challenging task. Various kinds of features have been developed over the years to increase the FLGPR detection performance. This paper focuses on investigating the use of as many features as possible for detecting buried targets and uses the sequential feature selection technique to automatically choose the features that contribute most for improving performance. Experimental results using data collected at a government test site are presented.

Paper Details

Date Published: 3 May 2016
PDF: 13 pages
Proc. SPIE 9823, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, 98231L (3 May 2016); doi: 10.1117/12.2224272
Show Author Affiliations
Darren Shaw, Univ. of Missouri (United States)
Kevin Stone, Univ. of Missouri (United States)
K. C. Ho, Univ. of Missouri (United States)
James M. Keller, Univ. of Missouri (United States)
Robert H. Luke, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Brian P. Burns, U.S. Army Night Vision & Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 9823:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
Steven S. Bishop; Jason C. Isaacs, Editor(s)

© SPIE. Terms of Use
Back to Top