Target matching in synthetic aperture radar imagery using a nonlinear optimization technique
Reuven Meth, Rama Chellappa · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
Recognition of targets in synthetic aperture radar (SAR) imagery is approached from the viewpoint of an optimization problem. Features are extracted from SAR target images and are treated as point sets. The matching problem is formulated as a non-linear objective function to maximize the number of matched features and minimize the distance between features. The minimum of this function is found using a deterministic annealing process. Registration is performed iteratively by using an analytically computed minimum at each temperature of the annealing. Thus, the images do not need to be initially registered as any translational error between them is solved for as part of the optimization. We have also extended the initial objective function to incorporate multiple feature classes. This matching method is robust to spurious, missing and migrating features. Matching results are presented for simulated XPATCH and real MSTAR SAR target imagery demonstrating the utility of this approach.