: . 无线电工程 ition, VMD)和精细复合多尺度散布熵(Refined Composite Multi-scale Dispersion Entropy, RCMDE)的 SEI 方法，利用 VMD 和 RCMDE 获取原始辐射源信号不同频率分量的多尺 度时间复杂度特征，选择 SVM 完成分类识别。仿真结果表明，莱斯信道下，在-5 dB 到 15 dB 的信噪比范 围内，所提方法对三个不同辐射源个体的识别准确率达到了 %，相比于其他方法有显著的性能提升。 关键词：变分模态分解，精细复合多尺度散布熵，特定辐射源识别 中图分类号：TN914 文献标识码：A A Specific Emitter Identification Method Based on VMD and RCMDE SONG Zihao1, CHENG Wei1, LI Jingwen 2, LI Xiaobai1 (1. Department of Early Warning Intelligence, Air Force Early Warning Academy, Wuhan 430019 China; 2. Teaching and Research Guarantee Center, Radar Sergeant School of Air Force Early Warning Academy, Wuhan 430000 China) Abstract: To solve the problems that the typical one-dimensional features commonly used in specific emitter identification (SEI) often lead to the decline of recognition performance, large dimensions of high-dimensional features and low computational efficiency when combined with general classifiers, an SEI method based on variational mode decomposition (VMD) and refined composite multi-scale scatter entropy (RCMDE) is proposed. VMD and RCMDE are used to obtain the multi-scale time complexity characteristics of different frequency components of the original emitter signal. Finally, SVM is selected to complete the classification. The simulation results show that in the range of signal-to-nois
