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| 基于融合熵特征的辐射源信号识别 | |
| 引用本文： | 余志斌,陈春霞,金炜东. 基于融合熵特征的辐射源信号识别[J]. 现代雷达, 2010, 32(1) |
| 作者姓名： | 余志斌 陈春霞 金炜东 |
| 作者单位： | 1. 西南交通大学信息科学与技术学院,成都,610031 2. 成都电子机械高等专科学校机械工程系,成都,610031 3. 西南交通大学电气工程学院,成都,610031 |
| 摘 要： | 针对相近雷达辐射源信号难以识别的问题,一种新的雷达辐射源信号识别方法被提出.该方法基于小波包分解,用主成分分析法融合含有信号类别特性的小波包重构系数特征,并将融合特征的能量熵和概率熵构成特征向量,基于支持向量机实现信号的分类识别.在较大信噪比(SNR)范围内,使用该方法能获得满意的正确识别率,当SNR为5 dB时,十分近似的线性调频信号正确识别率达到了91%,实验结果证实了该方法的有效性. |
| 关 键 词： | 小波包 PCA融合特征 雷达辐射源信号 概率熵 能量熵 |
Radar Emitter Signal Recognition Based on Fusion Entropy Features |
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| YU Zhi-bin,CHEN Chun-xi,JIN Wei-dongb. Radar Emitter Signal Recognition Based on Fusion Entropy Features[J]. Modern Radar, 2010, 32(1) | |
| Authors: | YU Zhi-bin CHEN Chun-xi JIN Wei-dongb |
| Affiliation: | YU Zhi-bin1a,CHEN Chun-xia2,JIN Wei-dong1b(1.a.School of Information Science & Technology,b.School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China)(2.Mechanical Engineering Department,Chengdu Electromechanical College,China) |
| Abstract: | Aiming at the problem of low degree of recognition in closed radars emitter signal recognition,a novel approach is proposed.In this approach,the fusion feature of wavelet packet reconstruction coefficient(WPRC)including characteristics of radar signal is extracted with the principal component analysis(PCA),and the fusion energy entropy(FEnEn)of the fusion feature and the fusion probability entropy(FPrEn)of the fusion feature are used to construct a feature vector,and the support vector machine is used to id... |
| Keywords: | wavelet package PCA fusion feature radar emitter signal probability entropy energy entropy |
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