Journal of Systems Engineering and Electronics ›› 2013, Vol. 35 ›› Issue (2): 282-286.doi: 10.3969/j.issn.1001-506X.2013.02.08

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Target recognition of SAR images using principal component analysis and sparse representation

LIU Zhong-jie1， ZHUANG Li-kui2， CAO Yun-feng2， DING Meng3   

  1. 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 
    2. Academy of Frontier Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 
    3. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Online:2013-02-08 Published:2010-01-03

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Abstract:

With the existing target recognition algorithms of synthetic aperture radar (SAR) images, image preprocessing, feature extraction and recognition algorithm are usually carried out. The adaptability of the preprocessing algorithm is difficult to be guaranteed. A target recognition algorithm using principal component analysis (PCA) and sparse representation is proposed. Firstly, the basic theory of sparse representation and reconstruction is presented. Secondly, an SAR image target recognition algorithm is presented using PCA and sparse representation. Finally, an experiment with five kinds of SAR target images in the MSTAR database is given. The simulation results show that this algorithm can still recognize the target effectively without preprocessing. Compared with the PCA and the thirdorder nearest neighbor algorithm, the proposed algorithm has a higher recognition rate and robustness.

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