| 基于小波包变换的辐射源信号特征提取和识别 |
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| 引用本文： | 王玲霞,袁佳,张效义.基于小波包变换的辐射源信号特征提取和识别[J].通信技术,2009,42(3):215-217. |
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| 作者姓名： | 王玲霞 袁佳 张效义 |
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| 作者单位： | 解放军信息工程大学通信工程系,河南,郑州,450002 |
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| 摘 要： | 文中基于小波包变换方法，对MSK信号辐射源提取了J-散度特征和能量特征，结合支持向量机分类器完成辐射源的识别，仿真结果表明：两者识别率均达到90％以上，从而验证了基于小波包变换的辐射源识别的有效性。
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| 关 键 词： | 小波包变换 特征提取 时频铺叠 |
Emitter Signals Feature Extraction and Recognition Based on Wavelet Packet Transform |
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| WANG Ling-xia,YUAN Jia,ZHANG Xiao-yi.Emitter Signals Feature Extraction and Recognition Based on Wavelet Packet Transform[J].Communications Technology,2009,42(3):215-217. |
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| Authors: | WANG Ling-xia YUAN Jia ZHANG Xiao-yi |
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| Affiliation: | (Information Engineering University, Zhengzhou Henan 450002, China) |
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| Abstract: | This paper mainly presents the algorithm based on wavelet packet transform in energy feature and J-divergence feature extraction of MSK signal, support vector machine （SVM） is utilized to implement emitters recognition, and the reliability of the two features is also compared, Simulations show that the accurate recognition ratio of the two features is above 90%, and indicate that the emitter recognition based on wavelet packet transform is effective. |
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| Keywords: | wavelet packet transform： feature extraction time-frequency tiling |
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