基于双谱的通信辐射源个体识别

Study of transmitter individual identification based on bispectra

对同类通信辐射源个体识别方法进行了深入的研究,采用选择双谱作为个体识别的基本特征向量,并融合了对分类具有显著贡献的辐射源特征参数,采用径向基神经网络分类器实现了对通信辐射源信号的个体分类识别。实验结果表明,该方法在较低信噪比条件下较好地解决了同类辐射源的个体识别问题,识别正确率优于90%。

Based on the bispectra and RBE a new method for identifying different transmitters of the same model was presented. The selected spectra and parameters significant for classification of the received signal form the identification feature vector, and RBF was used to realize the individual identification. Experiment results show that the method is able to classify the same model transmitter with an accuracy rate of no less than 90% under the environment of lower SNR.