Automatic vehicle target recognition in full SAR image scenes

A new method is presented for automatic target recognition in full synthetic aperture radar (SAR) image scenes. As SAR target classification is sensitive to target's azimuth, based on correlation filter theory and kernel feature analysis, a nonlinear correlation filter is provided, it can tolerate a distortion of target's azimuth. The novel filter exploits eigenvectors to reduce the dependence of the training set and extends the linear combination of eigenvectors nonlinearly to improve the classification performance. Moreover, to keep the computation tractable in high dimensional space, the kernel function is employed. The tests using MSTAR database demonstrate the scheme is practical and the novel filter implements target classification efficiently and accurately without templates and target poses estimation.