%0 Journal Article
%A QU Hua
%A ZHANG Rui-qing
%A ZHAO Ji-hong
%T Adaptive Beamforming Algorithm with Fast Convergence Speed
%D 2014
%R 10.13190/j.jbupt.2014.05.022
%J Journal of Beijing University of Posts and Telecommunications
%P 105-108
%V 37
%N 5
%X <p>The conventional least mean square (LMS) based adaptive beamforming converges very slowly under low signal-to-noise ratio (SNR), thus an adaptive beamforming algorithm in wavelet domain with a fast convergence rate was put forward. The white Gaussian noise could be erased by means of wavelet transform soft-threshold method. Besides, Newton's method was further applied in LMS algorithm for beamforming in wavelet domain. Simulation shows that the proposed algorithm indeed improve the convergence accuracy and the convergence rate compared with either the conventional LMS algorithm or the existed LMS algorithm in wavelet domain. It also substantially improves the accuracy of beamforming compared with the conventional LMS algorithm.</p>
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2014.05.022