Open AccessRobust adaptive beamforming method based on desired signal steering vector estimation and interference‐Plus‐noise covariance matrix reconstruction
Author(s) -
Huang Junsheng,
Su Hongtao,
Yang Yang
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0739
Subject(s) - adaptive beamformer , covariance matrix , signal (programming language) , control theory (sociology) , noise (video) , algorithm , computer science , beamforming , eigenvalues and eigenvectors , matrix (chemical analysis) , estimation of covariance matrices , covariance , estimator , mathematics , artificial intelligence , telecommunications , physics , statistics , materials science , control (management) , quantum mechanics , composite material , image (mathematics) , programming language
Here, the authors propose a robust adaptive beamforming method based on desired signal steering vector estimation and interference‐plus‐noise covariance matrix reconstruction, so as to attenuate the influences of the desired signal steering vector mismatch and the limited training snapshots on the performance of adaptive beamformer. More precisely, the desired signal steering vector is estimated by minimising the sine value of the angle between the presumed desired signal steering vector and the eigenvectors of sample covariance matrix. Besides, the sample covariance matrix is reconstructed by reducing the dispersion extent of the noise eigenvalues and eliminating the desired signal component from the sample covariance matrix. The proposed method can not only accelerate the convergence speed of adaptive beamforming algorithm, but also avoid the desired signal cancellation phenomenon when the desired signal is present in the training snapshots. Simulation results demonstrate the superiority of the proposed method.