一种分数低阶时频分解的盲波束形成算法

doi:10.3969/j.issn.1001-2400.2017.05.023

Abstract

Abstract:

A novel blind beamforming algorithm based on fractional lower-order time-frequency decomposition (TFD) is proposed to improve the performance of existing blind beamforming algorithms in impulsive noise environment. The traditional short-time Fourier transform (STFT) is first improved by utilizing fractional lower-order statistics to realize TFD in impulsive noise environment. Then, by combining the clustering method and the method for the uncertainty set, the TFD results of the receiving data at each sensor are used to realize the estimation of steering vectors (SV). Finally, the optimal weight coefficients of the proposed blind beamformer are achieved by substituting the estimated SV into the minimum variance distortionless response (MVDR) beamformer. Simulation results demonstrate that this algorithm can achieve superior output performance over the existing blind beamforming methods in impulsive noise environment. The proposed algorithm hardly needs any specific property of the receiving signals and can be more widely used.

Key words: time-frequency decomposition, fractional lower-order statistics, blind beamforming, symmetric alpha stable distribution

CHEN Pei;ZHAO Yongjun;LIU Chengcheng;LI Haiwen. Blind beamforming algorithm based on fractional lower-order time-frequency decomposition[J].Journal of Xidian University, 2017, 44(5): 134-139.

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Blind beamforming algorithm based on fractional lower-order time-frequency decomposition

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