SAR Automatic target recognition based on KPCA criterion
Han Ping①②; Wu Renbiao②; Wang Zhaohua①; Wang Yunhong③
①Institute of Electronic Information Eng., Tianjin University, Tianjin 300072, China;②Inst. of Comm. and Signal Proc.,Civil Aviation Univ. of China, Tianjin 300300, China;③Nat. Key Lab of Pattern Recognition, Inst. of Automation, CAS, Beijing 100080,China
Abstract：In this paper, SAR ATR (Synthetic Aperture Radar Automatic Target Recogni-tion) approach based on KPCA (Kernel Principal Component Analysis) is proposed. KPCA first maps the input data into some feature space using kernel functions and then performs lin-ear PCA on the mapped data. It takes the principal components in nonlinear space as sample features, then SVM classifier is used to classify targets. Experimental results with MSTAR SAR, data sets provided by the US DARPA/AFRL (Defense Advanced Research Projects Agency/Air Force Research Laboratory) show a better performance of classification and generalization.
2003, Vol. 25 
