标题:Chirplet-Atoms Network Approach to High-Resolution Range Profiles Automatic Target Recognition
作者:Li, Yifei ;Guo, Zunhua
作者机构:[Li, Yifei ;Guo, Zunhua ] School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China
会议名称:11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
会议日期:13 October 2018 through 15 October 2018
来源:Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
出版年:2019
DOI:10.1109/CISP-BMEI.2018.8633206
关键词:automatic target recognition; Chirplet-atoms network; high-resolution range profiles; neural networks
摘要:Since radar back-scattering from a real target can be very complex, a Chirplet-atoms network approach to automatic target recognition using high resolution range profiles (HRRP)is proposed in this paper. Based on the multilayer feed-forward neural network structure, the Chirplet-atom transform is used to the input layer for feature extraction, and the hidden layer and output layer constitute a classifier. The network weights and the parameters of Chirplet-atom node are simultaneously adjusted to achieve joint feature extraction and target classification. The simulation results of four aircrafts have shown that the Chirplet-atoms network approach has better recognition rates and noisy immunity. © 2018 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062819866&doi=10.1109%2fCISP-BMEI.2018.8633206&partnerID=40&md5=94d1763c4a1261dda913f7b9a0d80a10
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