Enhancements of pose-tagged partial evidence fusion SAR ATR

This paper discusses enhancements of a recently developed system for robust, obscured object recognition by means of Partial Evidence Reconstruction From Object Restricted Measures (PERFORM). PERFORM employs a partial evidence accrual approach to form both an object identity metric and an object pose estimate. Recent enhancements of PERFORM resulted in significant performance improvements over those reported in our previous publications. Partial evidence information is obtained by applying several instances of the authors Linear Signal Decomposition/Direction of Arrival (LSD/DOA) pose estimation technique, The LSD/DQA ATR system avoids search techniques (i.e. template matching) and is capable of detection and classification of possibly articulated, multiple objects with many degrees of freedom.(2) Development of PERFORM was motivated by the fact that pose estimation in the LSD/DOA method is primarily degraded in practice by the presence of background clutter in the pose estimation filter's region of support. The use of several independent pose estimators based upon LSD/DOA's Reciprocal Basis Set (RBS) filters constructed for overlapping sub-regions of the object, allow for clutter independent pose estimation, and robust detection of obscured targets, Recent enhancements of the partial evidence fusion have been focused on introducing subhypothesis decisions related to the occupancy of the various subregions by target or clutter and fusion of information for target occupied regions. Presented results include receiver operating characteristic (ROC) curves for Synthetic Aperture Radar (SAR) targets embedded in clutter with and without partial obscuration.