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小波空域相关ICA跳频信号盲分离算法
杜纯,周薇,高健,茹乐,孙毅
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(空军工程大学工程学院，西安 710038;长沙大学电子与通信工程系，长沙 410003;空军驻成都飞机工业公司军事代表室，成都 610092;空军驻上海胶带股份有限公司军事代表室，上海 200235)

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。

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

DOI：

基金项目:

A Spatial Correlation Based ICA Method for Frequency Hopping Signal Blind Separation

DU Chun,ZHOU Wei,GAO Jian,RU Le,SUN Yi

(The Engineering Institute, Air Force Engineering University, Xi′an 71003 8, China;Department of Electronic and Communication Engineering, Changsha University, C hangsha 410003, China;Air Force Military Delegation Office for Chengdu Aircraft Industry Co.,Ltd.,Ch engdu 610092, China;Air Force Military Delegation Office for Shanghai Adhesive Tape Co.,Ltd.,Sha nghai 200235, China)

Abstract:

A novel method of spatialcorrelation based independent component analy sis(ICA) using infomax algorithm is proposed and applied in the blind separati on and estimation of multiple frequency hopping(FH) signals. Simulation results show the proposed method posesses excellent features in faster convergence rate compared with traditional algorithm,can extract unmixing matrix without multi path signals,and has high antinoise performance.

Key words: FH communication spatial correlation independent component analysis(IC A) info max algorithm wavelet transform blind separation