Share Email Print

Proceedings Paper

Explosive hazard detection using MIMO forward-looking ground penetrating radar
Author(s): Darren Shaw; K. C. Ho; Kevin Stone; James M. Keller; Mihail Popescu; Derek T. Anderson; Robert H. Luke III; Brian P. Burns
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This paper proposes a machine learning algorithm for subsurface object detection on multiple-input-multiple-output (MIMO) forward-looking ground-penetrating radar (FLGPR). By detecting hazards using FLGPR, standoff distances of up to tens of meters can be acquired, but this is at the degradation of performance due to high false alarm rates. The proposed system utilizes an anomaly detection prescreener to identify potential object locations. Alarm locations have multiple one-dimensional (ML) spectral features, two-dimensional (2D) spectral features, and log-Gabor statistic features extracted. The ability of these features to reduce the number of false alarms and increase the probability of detection is evaluated for both co-polarizations present in the Akela MIMO array. Classification is performed by a Support Vector Machine (SVM) with lane-based cross-validation for training and testing. Class imbalance and optimized SVM kernel parameters are considered during classifier training.

Paper Details

Date Published: 15 May 2015
PDF: 14 pages
Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 94540Z (15 May 2015); doi: 10.1117/12.2177468
Show Author Affiliations
Darren Shaw, Univ. of Missouri-Columbia (United States)
K. C. Ho, Univ. of Missouri-Columbia (United States)
Kevin Stone, Univ. of Missouri-Columbia (United States)
James M. Keller, Univ. of Missouri-Columbia (United States)
Mihail Popescu, Univ. of Missouri-Columbia (United States)
Derek T. Anderson, Mississippi State Univ. (United States)
Robert H. Luke III, 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. 9454:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?