| 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
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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effect of the radar signal, the blind source separation algorithm based on the instantaneous linear mixture model is no longer applicable.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.
| [1] |
COMON P. Independent component analysis, a new concept?[J]. Signal Processing, 1994, 36(3): 287-314. doi: 10.1016/0165-1684(94)90029-9
|
| [2] |
张贤达. 现代信号处理[M]. 3版. 北京: 清华大学出版社, 2015: 367.
ZHANG X D. Modern signal processing[M]. 3rd ed. Beijing: Tsinghua University Press, 2015: 367 (in Chinese).
|
| [3] |
HYVÄRINEN A. Fast and robust fixed-point algorithms for independent component analysis[J]. IEEE Transactions on Neural Networks, 1999, 10(3): 626-634. doi: 10.1109/72.761722
|
| [4] |
BINGHAM E, HYVÄRINEN A. A fast fixed-point algorithm for independent component analysis of complex valued signals[J]. International Journal of Neural Systems, 2000, 10(1): 1-8. doi: 10.1142/S0129065700000028
|
| [5] |
王冬华, 杨吟华, 陈正禄, 等. 独立分量分析联合时域处理同频干扰抑制方法[J]. 现代防御技术, 2015, 43(5): 159-164. doi: 10.3969/j.issn.1009-086x.2015.05.026
WANG D H, YANG Y H, CHEN Z L, et al. Co-channel interference suppression based on joint independent component analysis and time domain[J]. Modern Defence Technology, 2015, 43(5): 159-164(in Chinese). doi: 10.3969/j.issn.1009-086x.2015.05.026
|
| [6] |
陈希信, 王峰, 龙伟军. 基于独立成分分析的外辐射源雷达同频干扰抑制[J]. 中国电子科学研究院学报, 2015, 10(1): 75-77. doi: 10.3969/j.issn.1673-5692.2015.01.012
CHEN X X, WANG F, LONG W J. Co-channel interference suppression for passive radar based on independent component analysis[J]. Journal of China Academy of Electronics and Information Technology, 2015, 10(1): 75-77(in Chinese). doi: 10.3969/j.issn.1673-5692.2015.01.012
|
| [7] |
YOU H, YU W Z, YOU H. Co-channel interference restraining for passive radar with illuminators of opportunity based on ICA[C]//2011 IEEE International Conference on Signal Processing, Communications and Computing. Piscataway: IEEE Press, 2011: 1-3.
|
| [8] |
吕晓德, 孙正豪, 刘忠胜, 等. 基于二阶统计量盲源分离算法的无源雷达同频干扰抑制研究[J]. 电子与信息学报, 2020, 42(5): 1288-1296. doi: 10.11999/JEIT190178
LÜ X D, SUN Z H, LIU Z S, et al. Research on suppressing co-channel interference of passive radar based on blind source separation using second order statistics[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1288-1296(in Chinese). doi: 10.11999/JEIT190178
|
| [9] |
袁梅, 牛奔, 董韶鹏, 等. 伪多源采样复域FastICA冲击定位算法[J]. 北京航空航天大学学报, 2016, 42(2): 243-250.
YUAN M, NIU B, DONG S P, et al. Pseudo-multi-source-sampling complex domain FastICA for impact location[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(2): 243-250(in Chinese).
|
| [10] |
SUN W H, LV Z, WU M C, et al. A comparative experimental study between instantaneous and convolutional BSS models for saccadic EOG signal separation[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 1-11.
|
| [11] |
TUTĂ L, NICOLAESCU M, ROSU G, et al. A robust adaptive filtering method based on independent component analysis (ICA)[C]//2020 13th International Conference on Communications (COMM). Piscataway: IEEE Press, 2020: 59-64.
|
| [12] |
戴前伟, 成沁宇, 冯德山. 基于FastICA的低信噪比探地雷达信号去噪[J]. 物探化探计算技术, 2017, 39(6): 727-735. doi: 10.3969/j.issn.1001-1749.2017.06.03
DAI Q W, CHENG Q Y, FENG D S. Low signal-noise ratio GPR signal denoising based on FastICA[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2017, 39(6): 727-735(in Chinese). doi: 10.3969/j.issn.1001-1749.2017.06.03
|
| [13] |
WANG H J, DUAN W Y, ZHAO H, et al. Research of night vision image denoising method based on the improved FastICA[C]//2017 IEEE International Conference on Mechatronics and Automation. Piscataway: IEEE Press, 2017: 332-336.
|
| [14] |
FOUDA M E, SHABOYAN S, ELEZABI A, et al. Application of ICA on self-interference cancellation of in-band full duplex systems[J]. IEEE Wireless Communications Letters, 2020, 9(7): 924-927. doi: 10.1109/LWC.2020.2973637
|
| [15] |
LIU J, SONG H, SUN H W, et al. High-precision identification of power quality disturbances under strong noise environment based on FastICA and random forest[J]. IEEE Transactions on Industrial Informatics, 2021, 17(1): 377-387. doi: 10.1109/TII.2020.2966223
|
| [16] |
XIANG Y, PENG D Z, UBHAYARATNE I, et al. Second-order cyclostationary statistics-based blind source extraction from convolutional mixtures[J]. IEEE Access, 2017, 5: 2011-2019.
|
| [17] |
ADALI T, HAYKIN S. Adaptive signal processing[M]. Hoboken: John Wiley & Sons, Inc. , 2010.
|
| [18] |
KOLDOVSKÝ Z, TICHAVSKÝ P. Gradient algorithms for complex non-Gaussian independent component/vector extraction, question of convergence[J]. IEEE Transactions on Signal Processing, 2019, 67(4): 1050-1064. doi: 10.1109/TSP.2018.2887185
|
| [19] |
贾雁飞. 独立分量分析及在信号提取中的应用研究[D]. 哈尔滨: 哈尔滨工程大学, 2018: 30.
JIA Y F. Research on independent component analysis and its application in extraction of signal[D]. Harbin: Harbin Engineering University, 2018: 30 (in Chinese).
|
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