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Proceedings Paper

Discrimination of civilian vehicles using wide-angle SAR
Author(s): Kerry E. Dungan; Lee C. Potter; Jason Blackaby; John Nehrbass
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Paper Abstract

At high frequencies, synthetic aperture radar (SAR) imagery can be represented as a set of points corresponding to scattering centers. Using a collection of sequential azimuths with a fixed aperture we build a cube of points for each of seven civilian vehicles in the Gotcha public release data set (GPRD). We present a baseline study of the ability to discriminate between the vehicles using strictly 2D geometric information of the scattering centers. The comparison algorithm is independent of pose and translation using a novel application of the partial Hausdorff distance (PHD) minimized through a particle swarm optimization. Using the PHD has the added benefit of reducing the effects of occlusions and clutter in comparing vehicles from pass to pass. We provide confusion matrices for a variety of operating parameters including azimuth extent, various amplitude cutoffs, and various parameters within PHD. Finally, we discuss extension of the approach to near-field imaging and to additional point attributes, such as 3D location and polarimetric response.

Paper Details

Date Published: 15 April 2008
PDF: 11 pages
Proc. SPIE 6970, Algorithms for Synthetic Aperture Radar Imagery XV, 69700Z (15 April 2008); doi: 10.1117/12.790440
Show Author Affiliations
Kerry E. Dungan, The Ohio State Univ. (United States)
Lee C. Potter, The Ohio State Univ. (United States)
Jason Blackaby, Wright State Univ. (United States)
John Nehrbass, Ohio Super Computer Ctr. (United States)

Published in SPIE Proceedings Vol. 6970:
Algorithms for Synthetic Aperture Radar Imagery XV
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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