New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM

Yun Lin, Xiao-Chun Xu, Zi-Cheng Wang

(College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China)



Abstract:

In this paper, according to the defect of methods which have low identification rate in low SNR, a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly, based on the theory of multi-resolution wavelet analysis, the wavelet power spectrum of non-cooperative signal can be gotten. Secondly, according to the information entropy theory, the wavelet power spectrum entropy is defined in this paper. Therefore, the database of signal’s wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally, the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual’s identification rate in low SNR, when the SNR is greater than 4 dB, the identification rate can reach 100％. Under unstable SNR conditions, when the range of SNR is between 0 dB and 24 dB, the average identification rate is more than 92.67％. Therefore, this method has a great application value in the complex electromagnetic environment.

Key words:  radiation source individual identification  wavelet power spectrum  information entropy  support vector machine

DOI：10.11916/j.issn.1005-9113.2014.01.014

Clc Number:TN911.6

Fund: