基于时频分布Rényi熵特征的雷达辐射源识别  

Radar emitter recognition based on rényi entropy of time-frequency distribution

作　　者：白航[1,2] 赵拥军[1] 沈伟[1] 徐永刚 

机构地区：[1]解放军信息工程大学信息工程学院 [2]61906部队

出　　处：《电路与系统学报》2013年第1期437-442,共6页Journal of Circuits and Systems

摘　　要：针对复杂体制雷达辐射源识别,提出一种基于时频分布Rényi熵的雷达信号特征提取和识别方法。该方法首先对雷达辐射源信号进行时频变换,然后提取信号时频分布的3阶、7阶和11阶Rényi熵作为特征向量,得到具有维数低、类间差异较大的识别特征。最后采用支持向量机分类器实现信号的分类识别。文中对8种常见雷达信号进行了仿真实验,结果表明在较大的信噪比范围内,该方法能获得较为满意的正确识别率,当信噪比为-3dB时,采用时频分布Rényi熵特征的平均识别率仍能达到90.75%,验证了提出方法的有效性。To correctly classify advanced radar emitter signals,a novel approach adopting Rényi Entropy of time frequency distribution for radar emitter signal recognition is proposed.Time-frequency distribution of radar emitter signals are obtained by using time-frequency reassignment transform,and then the third-order,seventh-order and eleventh-order Rényi Entropy of time-frequency distribution are used to construct a feature vector which has low dimensions and large between-class difference for radar signal recognition.Finally the support vector machine is used to identify radar emitter signals automatically.Simulation results show that the proposed approach can achieve satisfying accurate recognition over a wide range of SNR scenarios.Even for SNR=-3dB,the accurate recognition rate still achieves 90.75% by using Rényi Entropy of time-frequency distribution.The validity of the approach is demonstrated by experiments.

关 键 词：Rényi熵 时频重排 支持向量机 雷达辐射源识别 

分 类 号：TN974[电子电信—信号与信息处理]