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ReliefF算法在雷达辐射源信号识别中的应用 被引量：5

Application of ReliefF Algorithm in Radar Emitter Signal Recognition
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摘要 采用小波包变换提取雷达辐射源信号特征能够有效对信号进行识别,然而,由小波包变换提取的信号特征维数高,部分信号特征受噪声污染严重.基于此,采用ReliefF算法对信号特征的分类能力进行评价,选择出小波包中分类能力强的信号特征,再通过特征相关度算法去除分类能力相近的冗余特征,利用剩余的分类能力强的信号特征组成特征向量进行分类.仿真实验结果显示,该方法用较少的信号特征能够获得较高的正确识别率. Features extracted by wavelet packet transform can effectively identify signals, however, feature dimension of the features is high and some characteristics are seriously polluted by the noise. Classification ability of the features was evaluated by ReliefF algorithm and features with strong classification ability in wavelet packets were picked out. Then redundant features of similar classification ability were deleted by characteristic similarity algorithm. The remaining features of strong classification ability composed eigenvectors and they would be classified. Simulation experimental results show that this method using fewer features can obtain higher right recognition rate.
作者 杨志新 段美军
机构地区 西南交通大学信息科学与技术学院 西南交通大学电气工程学院
出处 《成都大学学报（自然科学版）》 2012年第2期151-153,共3页 Journal of Chengdu University（Natural Science Edition）
关键词 雷达辐射源信号 小波包变换 RELIEFF算法 雷达辐射源信号特征 radar emitter signal wavelet packet transform ReliefF algorithm features of radar emitter sig-nal
分类号 TN911.6 [电子电信—通信与信息系统]
  • 相关文献

参考文献6

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二级参考文献13

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共引文献34

同被引文献48

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引证文献5

二级引证文献25

成都大学学报（自然科学版）
2012年 第2期

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