SAR Target Feature Extraction and Recognition Based on Two-Stage 2DPCA

Hu Li-ping; Liu Hong-wei; Wu Shun-jun

doi:10.3724/SP.J.1146.2006.01919

Volume 30 Issue 7

Jan. 2011

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Hu Li-ping, Liu Hong-wei, Wu Shun-jun . SAR Target Feature Extraction and Recognition Based on Two-Stage 2DPCA[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1722-1726. doi: 10.3724/SP.J.1146.2006.01919

Citation:

Hu Li-ping, Liu Hong-wei, Wu Shun-jun . SAR Target Feature Extraction and Recognition Based on Two-Stage 2DPCA[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1722-1726. doi: 10.3724/SP.J.1146.2006.01919

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SAR Target Feature Extraction and Recognition Based on Two-Stage 2DPCA

doi: 10.3724/SP.J.1146.2006.01919

Received Date: 2006-12-04
Rev Recd Date: 2007-06-11
Publish Date: 2008-07-19

Abstract

Abstract

Feature extraction based on PCA for 2 dimensional images has the disadvantages of evaluating the covariance matrix accurately with great difficulty and high computational complexity, 2-dimensional PCA (2DPCA) overcomes these flaws. However, a drawback of 2DPCA is that it needs more features, since it only eliminates the correlations between rows. In this paper, two-stage 2DPCA is applied to further compress the dimensions of features and decrease the recognition computation. Experimental results performing on SAR ground targets based the Moving and Stationary Target Acquisition and Recognition (MSTAR) database indicate that two-stage 2DPCA combining with the pre-processing method in this paper not only decreases sharply feature dimensions, but increases recognition rate, and is robust to the variation of target azimuth.

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References(1)

References

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