基于参数估计和Kalman滤波的单通道盲源分离算法

doi:10.12305/j.issn.1001-506X.2024.08.32

Abstract

Abstract:

Aiming at the problem of single channel blind source separation (SCBSS) for communication signals with spectrum aliasing, a SCBSS algorithm based on parameter estimation and Kalman filtering is proposed. Firstly, in view of the limitation of root multiple signal classification (Root-MUSIC) algorithm in the estimation of similar carrier frequencies, an adaptive Root-MUSIC algorithm is proposed to estimate the number of source signals and carrier frequencies of the received blind mixed signals. Secondly, the idea of Kalman filtering is introduced into the SCBSS algorithm, and the signal model is constructed according to the estimated source signal parameters, which is used as the observation vector of the Kalman filtering system, and the two processes of "time update" and "measurement update" are performed to obtain the best estimation of the source signals and realize the single channel blind source separation. Simulation results show that the proposed algorithm can effectively and accurately separate multi-channel source signals from single channel received signal with spectrum aliasing, and has higher separation accuracy and faster operation speed than traditional algorithms.

Key words: single channel blind source separation (SCBSS), Kalman filtering, parameter estimation, communication signal processing

CLC Number:

TN911

Weihong FU, Yufei ZHOU, Xinyu ZHANG, Naian LIU. Single-channel blind source separation algorithm based on parameter estimation and Kalman filter[J]. Systems Engineering and Electronics, 2024, 46(8): 2850-2856.

Figures/Tables 8

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References 30

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算法	运行时间
EEMD	255.8
VMD	286.7
本文所提算法	36.4

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Single-channel blind source separation algorithm based on parameter estimation and Kalman filter

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