Shen, Q., Liu, W. orcid.org/0000-0003-2968-2888, Wang, L. et al. (1 more author) (2019) Group sparsity based target localization for distributed sensor array networks. In: 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12-17 May 2019, Brighton, United Kingdom. IEEE , pp. 4190-4194. ISBN 978-1-4799-8131-1
Abstract
The target localization problem for distributed sensor array networks where a sub-array is placed at each receiver is studied, and under the compressive sensing (CS) framework, a group sparsity based two-dimensional localization method is proposed. Instead of fusing the separately estimated angles of arrival (AOAs), it processes the information collected by all the receivers simultaneously to form the final target locations. Simulation results show that the proposed localization method provides a significant performance improvement compared with the commonly used maximum likelihood estimator (MLE).
Metadata
Item Type: | Proceedings Paper |
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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: | Distributed sensor array network; group sparsity; localization; angle of arrival; compressive sensing |
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 CHINA ELECTRONICS TECHNOLOGY GROUP CORPORATION UNSPECIFIED |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jun 2019 11:58 |
Last Modified: | 17 Apr 2020 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/icassp.2019.8683867 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145625 |