Li, D., Liu, W. orcid.org/0000-0003-2968-2888, Zakharov, Y. et al. (1 more author) (2023) Graph signal processing for narrowband direction of arrival estimation. In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) proceedings. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 04-10 Jun 2023, Rhodes Island, Greece. Institute of Electrical and Electronics Engineers (IEEE)
Abstract
For direction of arrival (DOA) estimation based on graph signal processing (GSP), it has been assumed that there is a phase shift between adjacent snapshots of the received signals. However, this assumption does not hold for narrowband signals and thus affects the performance of the corresponding algorithms. To improve the performance, a new GSP-based DOA estimation method is proposed. By building a periodic directed graph based on a graph shift operator and computing the spectrum using the Kronecker product, the relationship between the input narrowband signals and the graph adjacency matrix of different direction coefficients is constructed. Simulation results show that this method performs better than existing algorithms based on GSP.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. Except as otherwise noted, this author-accepted version of a paper subsequently published in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) proceedings is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Sensor arrays; DOA estimation; graph signal processing |
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) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/V009419/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 May 2023 13:18 |
Last Modified: | 04 Sep 2023 13:21 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/icassp49357.2023.10096068 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199066 |