摘要
提出了一种小波变换空域相关的信息极大化独立分量分析(ICA)超分离方法,并将其应用于多跳频信号的盲分离和参数估计中。理论分析及仿真结果表明,空域相关的ICA方法相对传统的ICA方法可较好地用于多跳频混合信号的分离与参数估计,且具有更快的收敛速度、无需多导信号即可求出解混矩阵、抗噪能力强等优点。
A novel method of spatial-correlation based independent component analysis(ICA) using info-rnax algorithm is proposed and applied in the blind separation and estimation of multiple frequency hopping(FH) signals. Simulation results show the proposed method posesses excellent features in faster convergence rote compared with traditional algorithm,can extract un-mixing matrix without multi-path signals,and has high anti-noise performance.
出处
《电讯技术》
北大核心
2010年第9期36-40,共5页
Telecommunication Engineering
关键词
跳频通信
小波空域相关
独立分量分析
信息极大化算法
小波变换
盲分离
FH communication
spatial-correlation
independent component analysis (ICA)
info-max algorithm
wavelet transform
blind separation