Identification of Individual Radio Transmitters Based on Selected Surrounding-line Integral Bispectra

A novel method of identifying individual radio transmitters with the same model is proposed in this paper. The selected surrounding-line integral bispectra are utilized as the main feature parameters, and they are interfused with parameters significant for classification of the received signal to form the identification feature vector. A support vector machine (SVM) based on Gaussian core-function is implemented to realize the individual identification. Experimental results demonstrate that the method is able to classify the same model radio transmitter with an accuracy rate under the environment where there is low SNR.