• Infrared and Laser Engineering
  • Vol. 51, Issue 10, 20220029 (2022)
Zhengwei Li1,2, Xiaobin Huang2,*, and Yao Hu2,*
Author Affiliations
  • 1School of Earth Science,Chengdu University of Technology, Chengdu 610059, China
  • 2The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, China
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    DOI: 10.3788/IRLA20220029 Cite this Article
    Zhengwei Li, Xiaobin Huang, Yao Hu. SAR ATR method based on canonical correlations analysis of features extracted by 2D random projection[J]. Infrared and Laser Engineering, 2022, 51(10): 20220029 Copy Citation Text show less

    Abstract

    Synthetic aperture radar (SAR) automatic target recognition (ATR) is an important support technology for modern battlefield intelligence reconnaissance and precision strikes. In order to improve the overall performance of SAR ATR, a method based on multiset canonical correlations analysis (MCCA) of two-dimensional (2D) projection features is proposed. First, a series of 2D random projection matrices are used to extract features from SAR images to obtain multi-level feature descriptions. Considering the correlation between these results and the possible redundancy and interference, they are further fused through MCCA to obtain a single feature vector. The sparse representation-based classification (SRC) is used to process the fusion feature vector to determine the target class. The experiment is carried out based on the MSTAR dataset to fully test the proposed methods. The experimental results verify its effectiveness.
    Zhengwei Li, Xiaobin Huang, Yao Hu. SAR ATR method based on canonical correlations analysis of features extracted by 2D random projection[J]. Infrared and Laser Engineering, 2022, 51(10): 20220029
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