Precision indoor three-dimensional visible light positioning using receiver diversity and multilayer perceptron neural network

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Mahmoud, Abdulrahman A. and Ahmad, Zahir and Haas, Olivier C. L. and Rajbhandari, Sujan (2020) Precision indoor three-dimensional visible light positioning using receiver diversity and multilayer perceptron neural network. IET Optoelectronics, 14 (6). pp. 440-446. ISSN 1751-8768 (https://doi.org/10.1049/iet-opt.2020.0046)

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Abstract

In recent times, several applications requiring highly accurate indoor positioning systems have been developed. Since the global positioning system is unavailable/less accurate in the indoor environment, alternative techniques such as visible light positioning (VLP) are considered. The VLP system benefits from the wide availability of illumination infrastructure, energy efficiency and the absence of electromagnetic interference. However, there is a limited number of studies on three dimensional (3D) VLP and the effect of multipath propagation on the accuracy of the 3D VLP. This study proposes a supervised artificial neural network to provide accurate 3D VLP whilst considering multipath propagation using receiver diversity. The results show that the proposed system can accurately estimate the 3D position with an average root mean square (RMS) error of 0.0198 and 0.021 m for line-of-sight (LOS) and non-LOS link, respectively. For 2D localisation, the average RMS errors are0.0103 and 0.0133 m, respectively.

ORCID iDs

Mahmoud, Abdulrahman A., Ahmad, Zahir, Haas, Olivier C. L. and Rajbhandari, Sujan ORCID logoORCID: https://orcid.org/0000-0001-8742-118X;
  • Item type:Article
    ID code:86948
    Dates:
    Date
    Event
    1 December 2020
    Published
    28 July 2020
    Accepted
    11 March 2020
    Submitted
    Notes:© 2020 The Institution of Engineering and Technology Mahmoud, A.A., Ahmad, Z.U., Haas, O.C. and Rajbhandari, S., 2020. Precision indoor threedimensional visible light positioning using receiver diversity and multi-layer perceptron neural network. IET Optoelectronics. (2020) https://dx.doi.org/10.1049/iet-opt.2020.0046
    Subjects:Science > Physics
    Department:Faculty of Science > Physics > Institute of Photonics
    Depositing user: Pure Administrator
    Date deposited:12 Oct 2023 13:38
    Last modified:12 Dec 2024 15:03
    URI:https://strathprints.strath.ac.uk/id/eprint/86948
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