基于张量正则分解的时频混叠信号欠定盲分离方法

doi:10.7527/S1000-6893.2014.0319

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基于张量正则分解的时频混叠信号欠定盲分离方法

艾小凡, 罗勇江, 赵国庆

西安电子科技大学电子信息攻防对抗与仿真技术教育部重点实验室, 西安 710071

收稿日期:2014-09-22 修回日期:2014-11-19 出版日期:2015-10-15 发布日期:2014-11-24
通讯作者: 罗勇江, Tel.: 029-88202274 E-mail: yjluo@mail.xidian.edu.cn E-mail:yjluo@mail.xidian.edu.cn
作者简介:艾小凡男, 博士研究生。主要研究方向: 电子侦察与信息对抗, 多维信号处理。 Tel: 029-88202274 E-mail: xiaofan_ai88@163.com;罗勇江男, 博士, 副教授, 硕士生导师。主要研究方向: 电子侦察与信息对抗, 宽带实时信号处理。 Tel: 029-88202274 E-mail: yjluo@mail.xidian.edu.cn;赵国庆男, 硕士, 教授, 博士生导师。主要研究方向: 电子侦察与信息对抗, 雷达信号处理。 Tel: 029-88202274 E-mail: guoqzhao@mail.xidian.edu.cn
基金资助:
中央高校基本科研业务费专项资金 (K5051302018)

Canonical decomposition approach for underdetermined blind separation of non-disjoint sources

AI Xiaofan, LUO Yongjiang, ZHAO Guoqing

Key Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi'an 710071, China

Received:2014-09-22 Revised:2014-11-19 Online:2015-10-15 Published:2014-11-24
Supported by:
Fundamental Research Funds for the Central Universities (K5051302018)

摘要/Abstract

摘要：

针对时频同时混叠条件下的欠定盲源分离(UBSS)问题,提出了一种基于四阶累积量(FO)与张量正则分解相结合的算法。首先构建观测到的混合信号的四阶累积量,并利用高阶累积量的"半不变性"将其表示成四阶张量的形式,然后采用线性搜索迭代最小二乘算法对张量进行分解并获得混合矩阵的估计,最后根据估计出的混合矩阵,采用最小均方误差波束形成器算法,完成源信号的恢复。仿真结果表明该方法的有效性,与已有算法相比提高了信号盲分离的性能。

关键词: 盲源分离, 欠定混合矩阵, 时频混叠, 四阶累积量, 张量正则分解

Abstract:

This paper proposes a method of underdetermined blind separation of non-disjoint sources (UBSS) based on fourth-order cumulant (FO) and tensor decomposition. By semi-invariance of high-order cumulant, the FO is presented as statistics of the observed signal as fourth-order tensor; hence the mixed matrix is estimated by tensor decomposition with line search alternating least square. Finally, with the estimated matrix, sources are recovered by minimum mean-squared error-based beamforming. Simulations illustrate the validity of the method and show that the proposed method outperforms the existing methods in performance significantly.

Key words: blind source separation, underdetermined mixtures, non-disjoint source, fourth-order cumulant, tensor canonical decomposition

中图分类号:

艾小凡, 罗勇江, 赵国庆. 基于张量正则分解的时频混叠信号欠定盲分离方法[J]. 航空学报, 2015, 36(10): 3393-3400.

AI Xiaofan, LUO Yongjiang, ZHAO Guoqing. Canonical decomposition approach for underdetermined blind separation of non-disjoint sources[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(10): 3393-3400.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于张量正则分解的时频混叠信号欠定盲分离方法

Canonical decomposition approach for underdetermined blind separation of non-disjoint sources

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