Open AccessWhite noise reduction for wideband linear array signal processing
Author(s) -
Anbiyaei Mohammad Reza,
Liu Wei,
McLer Des C.
Publication year - 2018
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2016.0730
Subject(s) - beamforming , wideband , computer science , noise (video) , white noise , signal (programming language) , signal processing , noise reduction , array processing , signal to noise ratio (imaging) , signal transfer function , electronic engineering , speech recognition , algorithm , telecommunications , analog signal , artificial intelligence , engineering , transmission (telecommunications) , image (mathematics) , programming language , radar
The performance of wideband array signal processing algorithms is dependent on the noise level in the system. A method is proposed for reducing the level of white noise in wideband linear arrays via a judiciously designed spatial transformation followed by a bank of highpass filters. A detailed analysis of the method and its effect on the spectrum of the signal and noise are presented. The reduced noise level leads to a higher signal‐to‐noise ratio for the system, which can have a significant beneficial effect on the performance of various beamforming methods and other array signal processing applications such as direction of arrival estimation. Here the authors focus on the beamforming problem and study the improved performance of two well‐known beamformers, namely the reference signal based and the linearly constrained minimum variance beamformers. Both theoretical analysis and simulation results are provided.