李彦兵, 杜兰, 刘宏伟, 徐丹蕾, 关永胜. 基于信号特征谱的地面运动目标分类[J]. 电波科学学报, 2011, 26(4): 641-648.
      引用本文: 李彦兵, 杜兰, 刘宏伟, 徐丹蕾, 关永胜. 基于信号特征谱的地面运动目标分类[J]. 电波科学学报, 2011, 26(4): 641-648.
      LI Yan-bing, DU Lan, LIU Hong-wei, XU Dan-lei, GUAN Yong-sheng. Moving ground targets classification based on eigenvalue sequence of echo signal[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2011, 26(4): 641-648.
      Citation: LI Yan-bing, DU Lan, LIU Hong-wei, XU Dan-lei, GUAN Yong-sheng. Moving ground targets classification based on eigenvalue sequence of echo signal[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2011, 26(4): 641-648.

      基于信号特征谱的地面运动目标分类

      Moving ground targets classification based on eigenvalue sequence of echo signal

      • 摘要: 研究低分辨、短驻留时间下地面运动车辆目标分类问题。根据微多普勒效应,使用多散射中心模型描述轮式和履带式车辆的微动部件雷达回波。指出目标回波中的谐波数是区分轮式和履带式车辆的一个稳定特征,由此提出一种基于目标回波信号特征谱的特征提取方法。该方法能够描述目标回波中的谐波信息,同时对于平动速度变化所带来的影响具有稳健性。使用仿真数据的实验结果验证了该方法的有效性,使用实测数据的实验结果表明:该方法在分类性能上优于基于主分量分析的分类方法。

         

        Abstract: This paper studieds the moving ground targets classification under the circumstances of low resolution and low dwell time. It establishes the echo signal model of micro-motion part using multi-scattering centre model based on micro-Doppler effect, which demonstrated that the number of harmonics contained in the echo signal is a stable feature to distinguish tracked vehicle and wheeled vehicle. Thus a new feature extraction method based on the eigenvalue sequence of the echo signal is proposed, which depicts the harmonic information of the echo signal, and is robust to the change of bulk velocity. The experimental results based on simulated data show the effectiveness of the proposed method and those based on measured data via Support Vector Machine (SVM) show the proposed method outperforms the principle component analysis (PCA) based method in classification performance.

         

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