SAR Image Target Recognition Method Combining Multi-Resolution Representation and Complex Domain CNN

2020 ◽  
Vol 57 (24) ◽  
pp. 241007
Author(s):  
乔良才 Qiao Liangcai
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
XiuXia Ji ◽  
Yinan Sun

It is necessary to recognize the target in the situation of military battlefield monitoring and civilian real-time monitoring. Sparse representation-based SAR image target recognition method uses training samples or feature information to construct an overcomplete dictionary, which will inevitably affect the recognition speed. In this paper, a method based on monogenic signal and sparse representation is presented for SAR image target recognition. In this method, the extended maximum average correlation height filter is used to train the samples and generate the templates. The monogenic features of the templates are extracted to construct subdictionaries, and the subdictionaries are combined to construct a cascade dictionary. Sparse representation coefficients of the testing samples over the cascade dictionary are calculated by the orthogonal matching tracking algorithm, and recognition is realized according to the energy of the sparse coefficients and voting recognition. The experimental results suggest that the new approach has good results in terms of recognition accuracy and recognition time.


Author(s):  
Jiaxin Tang ◽  
Fan Zhang ◽  
Fei Ma ◽  
Fei Gao ◽  
Qiang Yin ◽  
...  

2021 ◽  
pp. 104070
Author(s):  
Han Hongliang ◽  
Bai Yonglei ◽  
Lu Wei ◽  
Feng Fan ◽  
Wang Jianhua

2019 ◽  
Vol 28 (5) ◽  
pp. 1080-1086 ◽  
Author(s):  
Xingbin Wang ◽  
Jun Zhang ◽  
Shuaihui Wang

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