Cui, W., Shen, Q., Liu, W. orcid.org/0000-0003-2968-2888 et al. (1 more author) (2019) Low complexity DOA estimation for wideband off-grid sources based on re-focused compressive sensing with dynamic dictionary. IEEE Journal of Selected Topics in Signal Processing, 13 (5). pp. 918-930. ISSN 1932-4553
Abstract
Under the compressive sensing (CS) framework, a novel focusing based direction of arrival (DOA) estimation method is first proposed for wideband off-grid sources, and by avoiding the application of group sparsity (GS) across frequencies of interest, significant complexity reduction is achieved with its computational complexity close to that of solving a single frequency based direction finding problem. To further improve the performance by alleviating both the off-grid approximation errors and the focusing errors which are even worse for the off-grid case, a dynamic dictionary based re-focused off-grid DOA estimation method is developed with the number of extremely sparse grids involved in estimation refined to the number of detected sources, and thus the complexity is still very low due to the limited increased complexity introduced by iterations, while improved performance can be achieved compared with those fixed dictionary based off-grid methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 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. |
Keywords: | Direction-of-arrival estimation; Estimation; Wideband; Sensor arrays; Focusing; Complexity theory |
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: | 22 Aug 2019 08:25 |
Last Modified: | 10 Dec 2021 10:36 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/jstsp.2019.2932973 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150009 |