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出 处:《电子科学学刊》2000年第2期274-278,共5页
基 金:电科院预研基金
摘 要:高距离分辨雷达(HRR)的回波中蕴含丰富的目标信息,充分利用目标回波并采用恰当的特征抽取方法,可以有效地识别目标。本文提出一种利用相位信息和正则变换的目标识别方法。该方法基于雷达目标距离剖面像的幅度和相位矢量(幅相矢量),首先由各训练目标在不同方位姿态角时的幅相矢量构成综合矩阵并对之作正则变换建立正则子空间,然后将每类训练目标各方位姿态的幅相矢量向该子空间投影形成子像,取其平均结果作为该目标的库特征矢量。对未知目标,以其子像对库矢量的欧氏距离最小为分类准则,进行了识别模拟实验。The echo signal of a high-range-resolution radar(HRR) contains much information about target. By using this information and feature extraction method fully and properly, an efficient target recognition can be executed. A novel approach for radar target recognition is proposed in this paper. This approach explores canonical analysis on a matrix formed by the image vectors of training targets in different aspect angles. One image vector contains both the amplitudes and relative phases of the range profile of a target. A subspace is obtained from this analysis. Projection of an image vector into this subspace forms subimage. The subimages of a training target in different aspect angles are averaged into library feature vector for this target. Using the subimage of an unknown target as feature vector and minimum distance rule for target recognition, experiments on simulated data are done.
分 类 号:TN957.52[电子电信—信号与信息处理]
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