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所属单位：自动化学院
发表刊物：Xi Tong Cheng Yu Dian Zi Ji Shu/Syst Eng Electron
摘要：The dictionary learning model can really reflect radar high resolution range profile (HRRP) potential structural characteristics and the statistical modeling algorithm can effectively solve the HRRP attitude sensitivity problem. Based on those features, researches on the selection of atoms and the discriminant optimization problem for label consist K-singular value decomposition (LC-KSVD) have been carried out by using statistical modeling in dividing the HRRP's angular domain. Firstly, the maximum probability difference algorithm based on probabilistic principal component analysis is proposed to adapt HRRP angular domain to obtain the frame boundary. Secondly, based on LC-KSVD, the discriminant criterion is constructed by using the power spectrum of the frame boundary and the introduction of atomic sparse similarity error constraint in optimal dictionary selection to clarify test samples. The experimental results of the radar data show that this algorithm can improve the target recognition rate, and has good robustness to the noise interference. © 2018, Editorial Office of Systems Engineering and Electronics. All right reserved.
ISSN号：1001-506X
是否译文：否
发表时间：2018-04-01
合写作者：Yuan, Jiawen,张弓
通讯作者：刘文波