Electronic versions

  • Abdulrahman Abdullahi Mahmoud
  • Zahir Ahmad
  • Olivier Haas
  • Sujan Rajbhandari
    Huawei Technologies Sweden AB
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.
Original languageEnglish
Pages (from-to)440-446
Number of pages7
JournalIET Optoelectronics
Volume14
Issue number6
DOIs
Publication statusPublished - 1 Dec 2020
Externally publishedYes
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