基于小波变换的雷达辐射源信号特征提取

Feature extraction based on wavelet transform for radar emitter signals

摘要:

在小波多分辨分析的基础上提出一种对雷达辐射源信号进行脉内特征提取方法，该方法能够从信号中有效提取定量信息。将小波变换后低频逼近小波系数的能量分布熵，与经过尺度相关去噪计算后反映信号边缘的高频细节小波系数能量分布熵一起构成雷达辐射源信号的二维特征向量。通过对10种雷达辐射源信号的特征提取和分类仿真实验，结果表明：提取的样本特征在低信噪比下具有很好的抗噪性和可聚类性，证明了本文方法的有效性。

Abstract:

An approach for intra-pulse feature extraction of radar emitter signals was proposed based on the multi-resolution characteristics of wavelet transform. It was efficient to obtain quantitative information from signals. The energy entropy from approximation coefficients of wavelet transform and the other energy entropy from inter-scale correlations denoise of detail coefficients were adopted together as two-dimensional feature vectors. Experiment results demonstrated that the features of ten typical radar emitter signals extracted by wavelet transform showed good performance of noise-resistance and clustering when Signal-Noise Ratio(SNR) was low.