Two-Dimensional PCA for SAR Automatic Target Recognition
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.
Xiaoguang Lu Ping Han Renbiao Wu
Tianjin Key Lab for Advanced Signal Processing,P.O.Box 9,North Campus,Civil Aviation University of China,Tianjin,300300,P.R.China
国际会议
首届亚太合成孔径雷达会议(1st Asian and Pacific Conference on Synthetic Aperture Radar Proceedings)
安徽黄山
英文
2007-11-05(万方平台首次上网日期,不代表论文的发表时间)