摘要
在单通道通信系统抗干扰问题中,由于先验信息不足,不能采用常规的盲分离方法抑制干扰。针对此问题,提出一种小波分解结合独立分量分析(independent component analysis,ICA)的单通道盲分离抗干扰方法。该方法利用小波分解,将单路混合信号分解为一系列的小波分量,通过计算各层小波分量的能量,选择最优小波分量作为ICA的输入信号,采用ICA方法实现信号的分离和重构。该方法选择最优小波分量进行盲分离,有效减少分离算法的计算量,同时降低噪声对系统性能的影响。仿真结果表明,所提方法可以有效地分离混合信号,提高单通道通信系统的抗干扰能力和系统处理速度。
The traditional blind separation methods are not appropriate for anti-jamming in single-channel communication system due to the insufficiency of the prior information. In this paper, a new blind separation anti-jamming method based on wavelet decomposition and independent component analysis （ICA） is proposed for single-channel communication system. Wavelet decomposition process is employed to decompose the mixed signal into some non-overlapping wavelet components, and the optimum components are selected as the input of signals of the ICA in terms of component energy. The ICA is then applied to separate and recover the source signals from the received signal. Since only the optimum wavelet components get involved in separation algorithm, our method can significantly reduce the computation complexity while improve the resistance to noise. Simulation results show that the method can effectively separate the mixed signal in single-channel communication system, and the system running time is greatly shortened.
出处
《重庆邮电大学学报（自然科学版）》
CSCD
北大核心
2014年第5期648-653,共6页
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金
重庆市基础与前沿研究计划项目(cstc2013jcyjA40045)
重庆高校创新团队建设计划资助(KJTD201343)~~
关键词
单通道
抗干扰
小波分解
最优小波分量
独立分量分析(ICA)
single-channel
anti-jamming
wavelet decomposition
optimum components
independent component analysis （ICA）
