Wu, H., Shen, Q., Cui, W. et al. (1 more author) (2021) DOA estimation with nonuniform moving sampling scheme based on a moving platform. IEEE Signal Processing Letters, 28. pp. 1714-1718. ISSN 1070-9908
Abstract
The generalized linear moving sampling scheme (MSS) exploiting the second order statistics and also the high order cumulants is studied, where the set of MSS is defined as the shifted distance offsets involved in estimation based on a moving platform. Then, sparse physical arrays (SPAs) with nonuniform linear moving sampling schemes (NL-MSS), referred to as SPA-NL-MSS, are proposed to optimize the consecutive difference co-arrays. For the same number of sensors and data samples, better performance in terms of both the number of degrees of freedom (DOFs) and estimation accuracy can be achieved by SPA-NL-MSS than existing array structures exploiting array motions at the second order level.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 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: | moving platform; sparse array; difference coarray; DOA estimation; nonuniform moving sampling scheme |
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: | 19 Aug 2021 11:11 |
Last Modified: | 16 Aug 2022 00:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/lsp.2021.3105035 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177260 |