An Indoor Visible Light Positioning System Using Artificial Neural Network

Chun Lin, Bangjiang Lin, Xuan Tang, Zhenlei Zhou, Haiguang Zhang, Sushank Chaudhary, Zabih Ghassemlooy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

We propose a visible light positioning system based on an artificial neural network (ANN) and optical camera communications. The receiver's position is approximately and precisely estimated based on the decoded block coordinate and a typical back propagation ANN, respectively. The experimental results show that the proposed scheme offers a mean positioning error of 1.49 cm, which is required in many indoor positioning scenarios where high accuracy is essential.

Original languageEnglish
Title of host publication2018 Asia Communications and Photonics Conference, ACP 2018
PublisherOSA - The Optical Society
ISBN (Electronic)9781538661581
DOIs
StatePublished - 28 Dec 2018
Externally publishedYes
Event2018 Asia Communications and Photonics Conference, ACP 2018 - Hangzhou, China
Duration: 26 Oct 201829 Oct 2018

Publication series

NameAsia Communications and Photonics Conference, ACP
Volume2018-October
ISSN (Print)2162-108X

Conference

Conference2018 Asia Communications and Photonics Conference, ACP 2018
Country/TerritoryChina
CityHangzhou
Period26/10/1829/10/18

Keywords

  • Visible light communications (VLC)
  • artificial neural network (ANN)
  • indoor positioning
  • optical camera communications (OCC)

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