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ISAR image target recognition based on B(2D)2PGNMF


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ISAR image target recognition based on B(2D)2PGNMF
Wang FangSheng WeixingMa XiaofengWang Hao
School of Electronic Engineering and Optoelectronic Technology,NUST,Nanjing 210094,China
inverse synthetic aperture radar block two-directional and two-dimensional non-negative matrix factorization with projected gradient target recognition
In order to make use of local spatial structure information and classification information of inverse synthetic aperture radar(ISAR)to realize target recognition,a novel ISAR image target recognition algorithm based on block two-directional and two-dimensional non-negative matrix factorization with projected gradient(B(2D)2 PGNMF)is proposed here.Target image is constructed by the form of non-negative weighted combination of basis vectors.The weighted vectors resolved by the B(2D)2PGNMF are regarded as target features,and five-type aircraft targets are classified using a nearest neighbor classifier.The numerical results show:with the same compress ratios or dimensions of base matrix,the two-dimensional non-negative matrix factorization with projected gradient(PGNMF)has higher distinguishing accuracy than one-dimensional PGNMF; the distinguishing result of block non-negative matrix factorization with projected gradient(BPGNMF)is better than the PGNMF; the distinguishing result of the B(2D)2PGNMF is better than the two-directional and two-dimensional non-negative matrix factorization with projected gradient((2D)2PGNMF).With the same dimensions of base matrix,the compress ratio of the two-dimensional PGNMF is higher than that of the one-dimensional PGNMF,the running time of the BPGNMF is the longest and the running time of the(2D)2PGNMF is the shortest.This method has better recognition performance,and has no effect on operation efficiency.


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Last Update: 2013-12-31