Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification

Rajan Singh; Bhagavatula Vijaya Kumar

doi:10.1117/12.478684

1 August 2002 Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification

Rajan Singh, Bhagavatula Vijaya Kumar

Author Affiliations +

Proceedings Volume 4727, Algorithms for Synthetic Aperture Radar Imagery IX; (2002) https://doi.org/10.1117/12.478684
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

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Rajan Singh and Bhagavatula Vijaya Kumar "Performance of the extended maximum average correlation height (EMACH) filter and the polynomial distance classifier correlation filter (PDCCF) for multiclass SAR detection and classification", Proc. SPIE 4727, Algorithms for Synthetic Aperture Radar Imagery IX, (1 August 2002); https://doi.org/10.1117/12.478684

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