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Proceedings Paper

Target classification in synthetic aperture radar using map-seeking circuit technology
Author(s): Cameron K. Peterson; Patricia Murphy; Pedro Rodriguez
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Paper Abstract

Conventional target recognition approaches for SAR include template matching and feature-based classification. However, unlike visual imagery, Synthetic Aperture Radar (SAR) presents a unique challenge in that many attributes, such as scattering centers, are extremely pose dependent and wink in and out with even minor viewing geometry changes. This work implements a highly efficient biologically-inspired 3D template-based approach, the Map Seeking Circuit (MSC) algorithm, for target recognition in SAR. Instead of exhaustively searching a high dimensional state space, the MSC algorithm efficiently searches a superposition hypersurface to estimate target location and 3D pose. Results are shown from applying the algorithm to real SAR datasets.

Paper Details

Date Published: 4 May 2011
PDF: 10 pages
Proc. SPIE 8051, Algorithms for Synthetic Aperture Radar Imagery XVIII, 805113 (4 May 2011); doi: 10.1117/12.884015
Show Author Affiliations
Cameron K. Peterson, Johns Hopkins Univ. (United States)
Patricia Murphy, Johns Hopkins Univ. (United States)
Pedro Rodriguez, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 8051:
Algorithms for Synthetic Aperture Radar Imagery XVIII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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