Two-dimensional PCA for SAR automatic target recognition

被引：0

作者：

Lu, Xiaoguang ^{[1
]}

Han, Ping ^{[1
]}

Wu, Renbiao ^{[1
]}

机构：

[1] Civil Aviat Univ China, Tianjin Key Lab Adv Signal Proc, Tianjin 300300, Peoples R China

来源：

2007 1ST ASIAN AND PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR PROCEEDINGS | 2007年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

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.

引用

页码：513 / 516

页数：4

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