SAR ATR Via Pose-tagged Partial Evidence Fusion

This paper discusses the development and construction of a new system for robust, obscured object recognition by means of Partial Evidence Reconstruction From Object Restricted Measures (PERFORM). This new approach employs a partial evidence accrual approach to form both an object identity metric and an object pose estimate. The partial evidence information is obtained by applying several instances of the authors' Linear Signal Decomposition/Direction of Arrival (LSD/DOA) pose estimation technique. LSD/DOA is a means for estimating object pose for possibly articulated objects with multiple degrees of pose freedom that avoids the use of search mechanisms and template matching. Each instance of application of the LSD/DOA system results in a pose estimate and match metric aimed at recognition of a portion of a desired target. Each such partial object recognizer is formed in such a way as to be exposed to no clutter input when positioned over the target component of interest when no obscuration of the target is present. This work 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 lter's region of support. By exploiting several independent pose estimators based upon LSD/DOA's Reciprocal Basis Set (RBS) lters constructed for overlapping sub-regions of the object, we can construct a pose estimate that is independent of clutter in the unobscured case, and robust with respect to obscuration. Results presented here include receiver operating characteristic (ROC) curves for Synthetic Aperture Radar (SAR) targets embedded in clutter with and without partial obscuration.