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纪林章,庄海滔,程道来,等. 基于EEMD和FastICA的单通道背景声舱音盲源分离[J]. 应用技术学报,2021,21(1):62-67+74. DOI: 10.3969/j.issn.2096-3424.20064
引用本文: 纪林章,庄海滔,程道来,等. 基于EEMD和FastICA的单通道背景声舱音盲源分离[J]. 应用技术学报,2021,21(1):62-67+74. DOI: 10.3969/j.issn.2096-3424.20064
JI Linzhang, ZHUANG Haitao, CHENG Daolai, YI Chuijie. Blind Source Separation of Single-Channel Background Sound Cockpit Voice Based on EEMD and FastICA[J]. Journal of Technology, 2021, 21(1): 62-67, 74. DOI: 10.3969/j.issn.2096-3424.20064
Citation: JI Linzhang, ZHUANG Haitao, CHENG Daolai, YI Chuijie. Blind Source Separation of Single-Channel Background Sound Cockpit Voice Based on EEMD and FastICA[J]. Journal of Technology, 2021, 21(1): 62-67, 74. DOI: 10.3969/j.issn.2096-3424.20064

基于EEMD和FastICA的单通道背景声舱音盲源分离

Blind Source Separation of Single-Channel Background Sound Cockpit Voice Based on EEMD and FastICA

  • 摘要: 针对单通道信号盲源分离(blind source separation, BSS)模型的极端欠定问题,提出利用总体经验模态分解(ensemble empirical mode decomposition,EEMD)将单通道混合信号分解成多个瞬时频率本征模态函数(intrinsic mode function,IMF)分量的形式,构建新的观测矩阵,再通过快速独立分量分析(fast independent component analysis,FastICA)实现信号的盲源分离。仿真实验和实验室研究表明:该方法能够抑制宽频和瞬态干扰,有效地将淹没于噪声中的目标信号提取出来。实测数据分析表明该方法可以在飞机发动机噪声干扰下有效地提取背景声舱音信号,证明该方法在舱音信号处理中的有效性。

     

    Abstract: In order to solve the problem of extremely underdetermined blind source separation (BSS) with only one dimensional observing matrix, an ensemble empirical mode decomposition (EEMD) method is proposed to decompose the single-channel mixed signal into multiple instantaneous frequency intrinsic mode function (IMF). The new observing matrix is constructed, and then the blind source separation is realized by fast independent component analysis (FastICA). Simulation experiments and laboratory studies show that this method can suppress broadband and transient interference, and effectively extract the target signal submerged in noise. The analysis of the measured data shows that the method can effectively extract the background sound cockpit voice signal under the interference of aircraft engine noise, which proves the effectiveness of the method in the cockpit voice signal processing.

     

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