Target recognition in SAR images with Support Vector Machines (SVM)

摘要

This paper addresses object recognition problem in SAR images with SVM classifier; the work has been mainly focused on feature vector definition. Actually, each object is represented by a feature vector and SVM aims to estimate the best hyperplanes that separate classes in the feature space. Very robust definition of feature vector is proposed and tested on real data (MSTAR database). Confusion matrices prove that a very good recognition rate is reached, even for mixed incidence angles configuration.