Lan, X., Liu, W. orcid.org/0000-0003-2968-2888 and Ngan, H.Y.T. (Submitted: 2020) Study of four-dimensional DOA and polarisation estimation with crossed-dipole and tripole arrays. arXiv. (Submitted)
Abstract
Electromagnetic (EM) vector sensor arrays can track both the polarisation and direction of arrival (DOA) of the impinging signals. For linear crossed-dipole arrays, as shown by our analysis, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. For full four-dimensional (4-D, 2 DOA and 2 polarization parameters) estimation, we could extend the linear crossed-dipole array to the planar case. In this paper, instead of extending the array geometry, we replace the crossed-dipoles by tripoles and construct a linear tripole array. It is proved that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively in general and a dimension-reduction based MUSIC algorithm is developed so that the 4-D estimation problem can be simplified into two separate 2-D estimation problems, significantly reducing the computational complexity of the solution. The Cramr-Rao Bound (CRB) is also derived as a reference for algorithm performance. A brief comparison between the planar crossed-dipole array and the linear tripole array is performed at last, showing that although the planar structure has a better performance, it is achieved at the cost of increased physical size.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). For reuse permissions, please contact the Author(s). |
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: | 29 Sep 2020 13:39 |
Last Modified: | 30 Sep 2020 06:02 |
Published Version: | https://arxiv.org/abs/2004.08469v1 |
Status: | Submitted |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165932 |