改进的雷达高分辨距离像统计识别方法

基于雷达目标一维高分辨距离像的统计目标识别中,需解决两大问题:其一是如何处理距离像对姿态敏感和平移敏感；其二是如何准确地描述距离像的统计特征.直接将一维距离像用于目标识别通常很难取得好的识别效果.将高斯混合模型(GMM)应用到空中目标高分辨一维距离像统计建模中,提出了一种改进的高斯混合模型模糊聚类分析方法并用于目标识别.与传统的k-means聚类算法的仿真结果比较表明,该方法是有效、稳健的,在低信噪比条件下具有较好的识别效果.

Improved statistical identification method of high resolution range profiles

In the statistical target recognition based on radar High Resolution Range Profiles(HRRP),two challenging tasks are how to deal with the target-aspect and time-shift variation sensitivity of HRRP and how to accurately describe HRRPs statistical characteristics.It is difficult to obtain a satisfactory result by applying range profile to target identification directly.An improved fuzzy clustering analysis method based on Gaussian Mixture Mode(lGMM) is proposed and applied to the statistical modeling of HRRP.Compared with conventional k-means clustering algorithm,it is found that the current method can extract features independent of target orientation.Simulation results demonstrate the effectiveness and robustness of the proposed method,and SNR is low.