SAR Automatic target recognition based on KPCA criterion

Han Ping; Wu Renbiao; Wang Zhaohua; Wang Yunhong

Volume 25 Issue 10

Oct. 2003

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Han Ping, Wu Renbiao, Wang Zhaohua, Wang Yunhong. SAR Automatic target recognition based on KPCA criterion[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1297-1301.

Citation:

Han Ping, Wu Renbiao, Wang Zhaohua, Wang Yunhong. SAR Automatic target recognition based on KPCA criterion[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1297-1301.

Han Ping, Wu Renbiao, Wang Zhaohua, Wang Yunhong. SAR Automatic target recognition based on KPCA criterion[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1297-1301.

Citation:

Han Ping, Wu Renbiao, Wang Zhaohua, Wang Yunhong. SAR Automatic target recognition based on KPCA criterion[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1297-1301.

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SAR Automatic target recognition based on KPCA criterion

Han Ping^{①②;吴仁彪},
Wu Renbiao,
Wang Zhaohua,
Wang Yunhong

Received Date: 2002-07-09
Rev Recd Date: 2003-01-08
Publish Date: 2003-10-19

Abstract

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.

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References(1)

References

B. Scholkopf, A. Smola, K. R. Mller, Nonlinear component analysis as a kernel eigenvalueproblem, Neural Computation, 1998, 10(5), 1299-1319.[2]V.N. Vapnik.[J].Statistical learning theory, ATT Research, London University.1998,:-[3]E.R. Keydel, S. W. Lee, JT. Moore, MSTAR extended operating conditions, A Tutorial, SPIE,1996, 2757(3), 228-242.[4]Qun Zhao, DongXin Xu, J. C. Principe, Pose estimation of SAR automatic target recognition,Proceedings of Image Understanding Workshop, Monterey, CA., 1998, 11,827-832.[5]T. Ross, S. Worrell, V. Velten, J. Mossing, M. Bryant, Standard SAR ATR evaluation experimentusing the MSTAR public release data set, SPIE, 1998, 3370(4), 566-573.[6]Qun Zhao, J. C. Principe, Support vector machine for SAR automatic target recognition, IEEETrans. on Aerospace and Electronic Systems, 2001, 37(2), 643-654.

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