Wu, H., Shen, Q., Liu, W. orcid.org/0000-0003-2968-2888 et al. (1 more author) (2020) Underdetermined low-complexity wideband DOA estimation with uniform linear arrays. In: 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM). 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), 08-11 Jun 2020, Hangzhou, China. IEEE ISBN 9781728119472
Abstract
For a uniform linear array (ULA) with specially designed spacing and system settings, the received signals are first decomposed into different frequency bins via discrete Fourier transform (DFT). By grouping the frequencies of interest into several pairs, a generalized complexity reduction method is proposed to merge the redundant entries in both the auto-correlation matrices at each frequency and the cross-correlation matrices across different frequencies, followed by the group sparsity based low-complexity method to find the directions of arrival (DOAs) of the impinging signals. Simulation results demonstrate that significantly reduced complexity and improved performance can be achieved by the proposed method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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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: | 10 Nov 2020 11:57 |
Last Modified: | 10 Jun 2021 00:39 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/sam48682.2020.9104283 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:167836 |