Anbiyaei, M., Liu, W. orcid.org/0000-0003-2968-2888 and McLernon, D. (2018) White noise reduction for wideband linear array signal processing. IET Signal Processing, 12 (3). pp. 335-345. ISSN 1751-9675
Abstract
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 is presented. The reduced noise level leads to a higher signal to noise ratio (SNR) 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 (DOA) estimation. Here we focus on the beamforming problem and study the improved performance of two well-known beamformers, namely the reference signal based (RSB) and the linearly constrained minimum variance (LCMV) beamformers. Both theoretical analysis and simulation results are provided.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IET. This is an author produced version of a paper subsequently published in IET Signal Processing. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | White noise reduction; uniform linear arrays; nonuniform linear arrays; wideband beamforming; direction of arrival estimation; performance analysis |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Dec 2017 16:41 |
Last Modified: | 15 Dec 2023 16:52 |
Status: | Published |
Publisher: | Institution of Engineering and Technology |
Refereed: | Yes |
Identification Number: | 10.1049/iet-spr.2016.0730 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:124737 |