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卷积线性混合模型下的复非高斯信号盲源提取

李苗苗 吕晓德 王宁 刘忠胜

李苗苗,吕晓德,王宁,等. 卷积线性混合模型下的复非高斯信号盲源提取[J]. 北京航空航天大学学报,2023,49(1):212-219 doi: 10.13700/j.bh.1001-5965.2021.0197
引用本文: 李苗苗,吕晓德,王宁,等. 卷积线性混合模型下的复非高斯信号盲源提取[J]. 北京航空航天大学学报,2023,49(1):212-219 doi: 10.13700/j.bh.1001-5965.2021.0197
LI M M,LYU X D,WANG N,et al. Blind source extraction of complex non-Gaussian signals based on convolution linear mixture model[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):212-219 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0197
Citation: LI M M,LYU X D,WANG N,et al. Blind source extraction of complex non-Gaussian signals based on convolution linear mixture model[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):212-219 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0197

卷积线性混合模型下的复非高斯信号盲源提取

doi: 10.13700/j.bh.1001-5965.2021.0197
详细信息
    通讯作者:

    E-mail:lvxd@aircas.ac.cn

  • 中图分类号: TN973;TN958

Blind source extraction of complex non-Gaussian signals based on convolution linear mixture model

More Information
  • 摘要:

    雷达信号的多径效应导致基于瞬时线性混合模型的盲源分离算法不再适用。为此,提出了一种基于FastICA的复非高斯信号盲源提取方法。该方法将混合系统建模为卷积线性混合模型,使得信号模型中不需要将每个多径信号都看作一个独立的源信号,既节约了接收通道数量,又降低了盲源分离过程的复杂度,利用待提取信号的非高斯性实现高斯背景下复非高斯信源的提取。实验结果表明:在信干比为−30 dB时,所提方法能够快速、有效地处理卷积线性混合模型下复非高斯信源的提取问题,为该场景下的微弱信号提取提供了一种新的方法。

     

  • 图 1  复非高斯信源提取模型

    Figure 1.  Complex non-Gaussian source extraction model

    图 2  单个线性调频信号与高斯干扰信号混合

    Figure 2.  Mixture of single linear frequency modulation signal and Gaussian interference signal

    图 3  瞬时和卷积线性混合模型分离效果对比

    Figure 3.  Comparison of separation effect between instantaneous and convolution linear mixture models

    图 4  瞬时和卷积线性混合模型分离相关性对比

    Figure 4.  Comparison of separation correlation between instantaneous and convolution linear mixture models

    图 5  多线性调频信号盲源提取

    Figure 5.  Blind source extraction of multiple linear frequency modulation signals

    图 6  雷达脉冲回波数据盲源提取

    Figure 6.  Blind source extraction of radar pulse echo data

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出版历程
  • 收稿日期:  2021-04-15
  • 录用日期:  2021-07-04
  • 刊出日期:  2021-07-14

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