Abstract
Sophisticated modern radar systems have made it possible to build up detailed electromagnetic images of an object in the radar beam. This has generated interest in pattern recognition methods for radar target recognition. A feature of these high-resolution images is that some peaks relate to interactions between structures, as opposed to direct specular scattering. We propose a new method using interaction (multiple bounce) terms to compute a truly rotation-invariant feature for radar targets to be used for recognition. The effectiveness of the method is demonstrated by applying it to real data obtained from measurements in a compact range and demonstrating that the resulting feature sets could be used to effectively classify two similar target configurations.
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