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Proceedings Paper

Evaluation of MACH and DCCF correlation filters for SAR ATR using the MSTAR public database
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Paper Abstract

The MACH and DCCF correlation filter algorithms are evaluated using the publicly released MSTAR data base. These algorithms can be used as a matching engine for automatic target recognition in SAR imagery. In practice, the required filters can be synthesized using model based signature predictions. In addition, the MACH and DCCF algorithms are optimized to be robust to variations (distortions) in the target's signature. Unlike Matched Filtering or other exhaustive template based methods, the proposed approach requires very few filters. The paper describes the theory of the algorithm, key practical advantages and details of test results on the public MSTAR data base.

Paper Details

Date Published: 15 September 1998
PDF: 9 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321849
Show Author Affiliations
Abhijit Mahalanobis, Raytheon Missile System Co. (United States)
Daniel W. Carlson, Raytheon Missile System Co. (United States)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 3370:
Algorithms for Synthetic Aperture Radar Imagery V
Edmund G. Zelnio, Editor(s)

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