Confuser rejection performance of EMACH filters for MSTAR ATR

Abstract

Synthetic aperture radar (SAR) automatic target recognition (ATR) based on the extended maximum average correlation height (EMACH) distortion invariant filter (DIF) is presented. Prior work on the EMACH filter addresses 3-class and 10 class classification with clutter rejection. However, the ability of the EMACH filter to reject confusers is not well known. This paper addresses this. We follow a benchmark procedure which involves classification of three object classes over 360° aspect angle differences and with depression angle and variant differences and rejection of two unseen confusers from the Moving and Stationary Target Acquisition and Recognition (MSTAR) public database. We present a scheme to select which training set images to include while making the filters, since it is not necessary to use all training set images to make the filters. Results for classification with both confuser and clutter rejection are presented. We also compare our work with prior EMACH MSTAR work. We find EMACH filters to have poor confuser and clutter rejection. We also correct prior EMACH clutter rejection performance results.