Performance of an ATR index module against MSTAR data

We present a performance analysis of an indexing module contained in an automatic target recognition (ATR) system developed at Worcester Polytechnic Institute (WPI). The linear signal decomposition/direction of arrival (LSD/DOA) technique provides a low computational-cost indexing function for pose in ATR applications. The LSD/DOA technique forms a reduced-size, essential-information object data set which implicitly incorporates target and sensor variation specific data. To control the computational costs, the system consists of two independent components: a computationally expensive off-line component which forms the object representation and a computationally inexpensive on-line object recognition component. The size of the stored data set may also be adjusted providing a means to trade off complexity versus performance. Synthetic aperture radar (SAR) data collected as part of the Moving and Stationary Target Acquisition and Recognition (MSTAR) program has been released to the public, providing an opportunity for ATR performance assessment against a standard high quality data set. We present the results of a number of simulated tests against the MSTAR public database to demonstrate the performance of the LSD/DOA index module on a given target along with the performance of the WPI ATR itself as a function of the depression angle and target configuration