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

被引：0
|
作者：
Li M. [1 ,2 ,3 ]
Lyu X. [1 ,2 ]
Wang N. [1 ,2 ,3 ]
Liu Z. [1 ,2 ]
机构：
[1] Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing
[2] National Key Lab of Microwave Imaging Technology, Beijing
[3] University of Chinese Academy of Sciences, Beijing
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2023年 / 49卷 / 01期
关键词：
blind source extraction; complex FastICA algorithm; convolution linear mixing; multipath effect; non-Gaussian signal;
D O I：
10.13700/j.bh.1001-5965.2021.0197
中图分类号：
学科分类号：
摘要：
Due to the multipath effect of the radar signal, the blind source separation algorithm based on the instantaneous linear mixture model is no longer applicable. A blind source extraction method for complex non-Gaussian signals based on the FastICA algorithm is proposed. The mixed system is modeled as a convolutional linear mixture model, so that each multipath signal does not need to be regarded as an independent source signal in the signal model, which not only saves the number of receiving channels, but also reduces the complexity of blind source separation process. The non-Gaussian feature of the signal to be extracted is used to extract complex non-Gaussian sources in Gaussian background. The experimental results show that when the signal to interference ratio is −30 dB, the proposed method can quickly and effectively deal with the extraction of complex non-Gaussian sources in the convolutional linear mixture model, which provides a new method for weak signal extraction in this scene. © 2023 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
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页码：212 / 219
页数：7
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