适于一维散射中心识别的模糊分类器
A Fuzzy Classifier for Radar Target Recognition Using One-Dimensional Scattering Centres
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摘要: 该文研究了雷达目标一维散射中心的提取及其特性,针对一维散射中心的特点,提出了一种基于模糊分布的分类器。该分类器对特征矢量长度没有一致性要求,并可根据测试样本灵活选择训练样本,有效地解决了以一维散射中心为特征的识别问题。Abstract: In this paper, one-dimensional scattering centre extraction of radar targets is reviewed. A new classifier based on fuzzy distribution is proposed, which is very much suitable for one-dimensional scattering centre classification. The fuzzy classifier does not require the feature vectors to have the same dimension and allows the training samples to be flexibly chosen for different test samples. Theoretical analysis and simulation results show that the proposed fuzzy classifier can efficiently solve the problem of radar target recognition using one-dimensional scattering centres.
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