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基于联合时频特征和HMM的多方位SAR目标识别
引用本文:张新征,黄培康. 基于联合时频特征和HMM的多方位SAR目标识别[J]. 系统工程与电子技术, 2010, 32(4): 712-717
作者姓名:张新征  黄培康
作者单位:(目标与环境电磁散射辐射国防科技重点实验室, 北京 100854)
摘    要:研究了联合时频特征和隐马尔科夫模型(hidden Markov model, HMM)的多方位合成孔径雷达(synthetic aperture radar, SAR)目标识别方法。利用HMM模型可以有效地对多方位SAR目标特征分析及识别。在HMM多方位SAR目标识别中的关键之一是SAR目标回波高分辨率距离像(high resolution range profile, HRRP)的特征提取。提出了一种时变频因子加权Fisher鉴别的特征提取方法。利用MSTAR实测SAR目标数据集进行了特征提取和识别实验,实验结果验证了方法的有效性。

关 键 词:合成孔径雷达  时频特征  隐马尔科夫模型  目标识别

Multi-aspect SAR target recognition based on combined time-frequency feature and HMM
ZHANG Xin-zheng,HUANG Pei-kang. Multi-aspect SAR target recognition based on combined time-frequency feature and HMM[J]. System Engineering and Electronics, 2010, 32(4): 712-717
Authors:ZHANG Xin-zheng  HUANG Pei-kang
Affiliation:(National Electromagnetic Scattering Laboratory, Beijing 100854, China)
Abstract:Multi-aspect sythetic aperture radar(SAR) target recognition based on combined time-frequency feature and hidden Markov model(HMM) is investigated.HMM is a powerful tool to analyze and recognize the characteristics of multi-aspect SAR targets as a framework.One of the critical technique is feature extraction from the high resolution range profile(HRRP) of target echoes in the framework.A time-varying frequency factor weighted Fisher discrimination time-frequency spectra feature extraction method is proposed...
Keywords:synthetic aperture radar (SAR)  time-frequency feature  hidden Markov model (HMM)  target recognition
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