Model-based SAR ATR System

Recognizing a target in synthetic-aperture radar (SAR) images is an important, yet challenging, application of the model-based vision technique. This paper describes a model-based SAR recognition system based on invariant histograms and deformable template matching techniques. An invariant histogram is a histogram of invariant values defined by geometric features such as points and lines in SAR images. Although a f a v invariances are sufficient to recognize a target, we build a histogram of all invariant values given by all possible target feature pairs. This redundant histogram enables robust recognition under severe occlusions typical in SAR recognition scenarios. Multi-step deformable template matching examines the existence of an object by superimposing templates over potential energy field generated fiom images or primitive features. It determines the template configuration which has the minimum deformation (deformation energy) and the best alignment of the template with features (potential energy). The deformability of the template absorbs the instability of SAR features. We have implemented the system and evaluated the system performance using hybrid SAR images, generated from synthesized model signatures and real SAR background signutures.1ntroduction T h i s research was sponsored in part by the U.S. Advanced Research Project Agency under Wright Research and Development Center, U.S. Air Force under Contract M3615-93-11282, in part by the U.S. Advanced Research Project Agency under Army Research Office, the Department of the Army under Grant DAAHOQ-94-G-0006, and in part by the office of Naval Research. the Department of the Navy under Grant N00014-931 1220. Views and conclusions contained in this document are those of the authors and should not be interpreted as necessary representing official policies or endorsements, either expressed or implied, of the Department of the Air Force, the Department of the Army, the Department of the Navy or the United States Government.