利用小波变换特征提取的通信辐射源个体识别方法

为解决非协作通信条件下对通信辐射源的个体识别问题，提出了一种基于小波变换特征提取的个体识别方法。该方法对非协同通信的接收信号进行小波变换，通过计算类间分离度筛选最优小波基提取特征向量，并根据特征分布选取特定小波基下的小波系数复杂度作为信噪比参考值辅助个体识别。仿真结果表明，在信噪比变化的环境中及通信辐射源个体差异较小的情况下有较好的识别效果，从而验证了该方法的有效性。 

specific emitter identification using wavelet transform feature extraction

In order to solve the problem of individual identification of communication radiation sources under non-cooperative communication conditions, a specific emitter identification method using wavelet transform feature extraction is proposed. The method performs wavelet transformation on the received non-cooperative communication signal, and select the optimal wavelet basis which is used to extract feature vectors by calculating the degree of separation between classes, then according to the feature distribution select the wavelet coefficient complexity under specific wavelet basis as the SNR reference value to assist individual identification. The simulation results show that the recognition effect is better in the environment where the SNR changes and the individual differences of communication radiation sources are small, thus verifying the effectiveness of the method.