采用ICA的公共信道多干扰源信号的自动识别方法  

Automatic recognition of multi-interference source signals in the common channel based on independent component analysis

作　　者：张鹏伟[1] 

机构地区：[1]陕西科技大学电气与信息工程学院,陕西西安710021

出　　处：《智能系统学报》2013年第3期277-282,共6页CAAI Transactions on Intelligent Systems

摘　　要：为解决公共信道中多个干扰信号自动识别的问题,提出了采用独立分量分析(ICA)的多干扰源盲信号分离技术.该方法先对混合的干扰信号进行分离,然后对每路信号和干扰在时域、频域和高阶累积域进行特征提取和自动识别.以4种干扰信号和2种通信信号共信道混合为例进行了仿真实验,仿真结果中该方法迭代5次达到收敛,收敛时的性能指数为0.21,说明信号分离效果较好.当信噪比高于10 dB时,正确分离率达到95%以上;当信噪比低于10 dB时,分离率变化不大而识别率大大下降,由此表明了该方法的正确性和有效性.A new method was presented to solve the problem of automatic recognition of multi-interfering signals in the common channel. Based on the independent component analysis （ICA） , the multi-interfering blind signal sepa- ration technology was adopted to separate the interfering signals, which are mixed at the same time. Also the algo- rithm selected the features of each signal and interference in time domain, frequency domain and high-order cumu- lant domain to complete the recognition of the interfering signals. The computer simulation utilizes the automatic rec- ognition method to solve the problem of two types of signals and four interferences mixed in the same channel, and the results show that after five times of iteration the algorithm achieves convergence with a good performance index of 0.21. The results also indicate that when SNR is more than 10 dB, the accurate interference separation rate is a- bove 95%. And when SNR is less than 10 dB, the recognition rate drops greatly while the separation rate is hardly influenced, which proves the correctness and validity of this method.

关 键 词：多干扰源信号 信号识别 盲信号分离 独立分量分析 公共信道 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] TN911[自动化与计算机技术—计算机科学与技术]