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 pro-file,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 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.Recognition experiments are performed by the feature extraction method and HMM,which shows that the performance of this feature extraction method is effective.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2010年第4期712-717,共6页
Systems Engineering and Electronics
关键词
合成孔径雷达
时频特征
隐马尔科夫模型
目标识别
synthetic aperture radar（SAR）
time-frequency feature
hidden Markov model（HMM）
target recognition
