A Multiview SAR Target Recognition Method Using Inner Correlation Analysis

被引:1
作者
Lei, Lei [1 ]
Guo, Dongen [1 ]
Feng, Zhihui [2 ]
机构
[1] Nanyang Inst Technol, Sch Comp & Software, Nanyang 473000, Peoples R China
[2] Henan Agr Univ, Coll Informat & Management Sci, Zhengzhou 450002, Peoples R China
关键词
JOINT SPARSE REPRESENTATION; IMAGES; CLASSIFICATION; FUSION; MULTIPLE;
D O I
10.1155/2021/9703709
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper proposes a synthetic aperture radar (SAR) image target recognition method using multiple views and inner correlation analysis. Due to the azimuth sensitivity of SAR images, the inner correlation between multiview images participating in recognition is not stable enough. To this end, the proposed method first clusters multiview SAR images based on image correlation and nonlinear correlation information entropy (NCIE) in order to obtain multiple view sets with strong internal correlations. For each view set, the multitask sparse representation is used to reconstruct the SAR images in it to obtain high-precision reconstructions. Finally, the linear weighting method is used to fuse the reconstruction errors from different view sets and the target category is determined according to the fusion error. In the experiment, the tests are conducted based on the MSTAR dataset, and the results validate the effectiveness of the proposed method.
引用
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页数:7
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