基于联合时频特征和HMM的多方位SAR目标识别

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。

Multi-aspect SAR target recognition based on combined time-frequency feature and HMM

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...