计算机应用研究2017，Vol.34Issue(4)：1172-1175,4.DOI:10.3969/j.issn.1001-3695.2017.04.049
基于固有时间尺度分解模型的通信辐射源特征提取算法
Feature extraction algorithm based on intrinsic time-scale decomposition model for communication transmitter
摘要
Abstract
Aiming at the problem of low accuracy of individual identification method for current communication emitter,and the problem of low feature extraction efficiency,this paper proposed a method for extracting the features of communication transmitter based on intrinsic time-scale decomposition (ITD) model.The algorithm extracted the original signal bispectrum characteristics,proper rotation components combined with the fractal characteristics of the instantaneous amplitude spectrum characteristics of vector,and used support vector machine (SVM) to get classification results.Through six actual communication transmitters classification experiment results show that the algorithm can still get better classification results without any priori information about the transmitters,and has a certain degree of improvement in recognition accuracy and computational efficiency comparing to the method of feature extraction based on empirical mode decomposition (EMD).关键词
通信辐射源/特征提取/时间尺度分解/时频分析Key words
communication transmitter/feature extraction/intrinsic time-scale decomposition/time-frequency analysis分类
信息技术与安全科学引用本文复制引用
桂云川,杨俊安,吕季杰..基于固有时间尺度分解模型的通信辐射源特征提取算法[J].计算机应用研究,2017,34(4):1172-1175,4.基金项目
安徽省自然科学基金资助项目(1308085QF99,1408085MKL46) （1308085QF99,1408085MKL46）
