Lan, X. and Liu, W. orcid.org/0000-0003-2968-2888 (2019) Direction finding for a mixture of single-transmission and dual-transmission signals. In: Proceedings of the 2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). 2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 10-12 Dec 2019, Ajman, United Arab Emirates. IEEE ISBN 9781728153421
Abstract
Currently, most of existing research in direction of arrival (DOA) estimation is focused on single signal transmission (SST) based signal. However, to make full use of the degree of freedom provided by the system in the polarisation domain, the dual signal transmission (DST) model has been adopted more and more widely in wireless communications. In this work, a DOA estimation method for a mixture of SST and DST signals (referred to as the mixed signal transmission (MST) model) is proposed. To our best knowledge, this is the first time to study the DOA estimation problem for such an MST model. There are two steps in the proposed method, which deals with the two kinds of signals separately. The performance of the proposed method is compared with the Cramér-Rao Bound (CRB) based on computer simulations.
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: | eess.SP; eess.SP |
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: | 08 Jan 2020 15:39 |
Last Modified: | 20 Feb 2021 01:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ISSPIT47144.2019.9001893 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154977 |