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Proceedings Paper

Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification
Author(s): Rajan Singh; Bhagavatula Vijaya Kumar
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Paper Abstract

The Extended Maximum Average Correlation Height (EMACH) filter and the Polynomial Distance Classifier Correlation Filter (PDCCF) are applied to the Moving and Stationary Target Acquisition and Recognition (MSTAR) database for detection and classification. Filter performance is evaluated for a ten-class problem. The generalization capabilities are examined by conducting tests for targets differing by serial numbers, in-plane rotation, and depression angle. For comparison, results were also obtained using the Maximum Average Correlation Height (MACH) filter, Distance Classifier Correlation Filter (DCCF), and Optimal Trade-off Synthetic Discriminant Function (OTSDF) filter.

Paper Details

Date Published: 1 August 2002
PDF: 12 pages
Proc. SPIE 4727, Algorithms for Synthetic Aperture Radar Imagery IX, (1 August 2002); doi: 10.1117/12.478684
Show Author Affiliations
Rajan Singh, Carnegie Mellon Univ. (United States)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 4727:
Algorithms for Synthetic Aperture Radar Imagery IX
Edmund G. Zelnio, Editor(s)

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