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
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.