Journal of Terahertz Science and Electronic Information Technology , Volume. 21, Issue 2, 183(2023)
Application of nonlinear correlation information entropy to selection of multiple features and SAR target recognition
The multiple features are selected and classified based on Nonlinear Correlation Information Entropy(NCIE) for the target recognition problem of Synthetic Aperture Radar(SAR) image. The Gaussian mixture model is employed to model the probability distributions of different kinds of features and then the KL(Kullback-Leibler) divergence is utilized to evaluate the similarity among different kinds of features. The NCIE values of different combinations of features are calculated and the one with the maximum entropy is chosen as the optimal. The joint sparse representation model is employed to represent and classify the selected features. Experiments are conducted based on the MSTAR data under the standard operating condition and extended operating condition. The results show the effectiveness of the proposed method.
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HE Jie, LI Wenjuan, CHEN Xin. Application of nonlinear correlation information entropy to selection of multiple features and SAR target recognition[J]. Journal of Terahertz Science and Electronic Information Technology , 2023, 21(2): 183
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Received: May. 9, 2020
Accepted: --
Published Online: Mar. 16, 2023
The Author Email: Wenjuan LI (sunflower_xpj@163.com)