Two-Dimensional PCA for SAR Automatic Target Recognition

摘要

In this paper, a new technique for Synthetic Aperture Radar (SAR) automatic target recognition (ATR) is developed, which is builded upon Two-Dimensional Principle Component Analysis (2DPCA). First, 2DPCA is applied to extract features in frequency domain, which is based on image matrix directly. Then support vector machine (SVM) is used for classification. Experimental results on MSTAR dataset show that the 2DPCA method both gives higher recognition rate, and are computationally more efficient than PCA.