基于经验模态分解特征的无线电引信抗扫频式干扰方法

To slove the current problem of the weakness of radio FM fuses against frequency-sweeping jamming signals in the complex electromagnetic battlefield environment, a method of radio FM fuse against frequency-sweeping jamming signals based on empirical mode decomposition (EMD) features was proposed. Based on the target and the output signal of the frequency-sweeping FM radio fuse detection, EMD decomposition was used to obtain 10 layers of intrinsic mode function (IMF) components, the energy share of the intrinsic mode function, energy aggregation and Renyi entropy features in each layer of IMF components were extracted, and principal components analysis (PCA) algorithm was used for feature dimensionality reduction to ensure that the cumulative explanation of the difference was over 95%, and the reduced feature matrix was used as the input of the support vector machine (SVM) to classify and identify the target and sweeping interference signals. The experimental results show that the proposed method can effectively classify and identify targets and sweeping interfering signals, and the classification accuracy can reach 98.06%±0.003 8, the target detection rate can reach 96.65%±0.003 7, and the false alarm rate is 3.35%±0.003 7.