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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