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Proceedings Paper

Analyzing three dimensional radar voxel data using the discrete Fourier transform for SAEH detection
Author(s): P. Plodpradista; D. K. C. Ho; J. M. Keller; M. Popescu; A. Buck
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Paper Abstract

The detection of side-attack explosive hazards (SAEHs) is a challenging task especially if the SAEHs are camouflaged. Three-Dimensional Radar is one of the most prominent sensors that has shown a great capacity for detecting concealed SAEHs. This system produces high-resolution volumetric images where each voxel’s intensity represents the radar signal return at a specific point in the three-dimensional space. It has the capability to enhance the signal response from a SAEH nested in camouflage materials and suppress the interference from the surroundings. Nevertheless, processing the radar data in the spatial domain has some limitations in differentiating SAEH from clutter objects. In this paper, we propose the use of the discrete Fourier transform (DFT) to analyze the voxel data and capture the spatial frequency characteristics of the radar signal from SAEHs. Through a machine learning approach, our proposed algorithm is able to identify the frequency signatures of SAEHs and to differentiate them from anomalies caused by the background or clutter. This approach yields a confidence value indicating the likelihood of a SAEH at a particular location. The detection ability of the proposed algorithm is demonstrated by the receiver operating characteristic (ROC) curves generated using a dataset collected from a U.S. Army test site.

Paper Details

Date Published: 30 April 2018
PDF: 9 pages
Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 1062814 (30 April 2018); doi: 10.1117/12.2304380
Show Author Affiliations
P. Plodpradista, Univ. of Missouri (United States)
D. K. C. Ho, Univ. of Missouri (United States)
J. M. Keller, Univ. of Missouri (United States)
M. Popescu, Univ. of Missouri (United States)
A. Buck, Univ. of Missouri (United States)

Published in SPIE Proceedings Vol. 10628:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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