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

6 Citations (Scopus)

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)
PublisherIEEE
ISBN (Electronic)978-1-5386-6158-1
ISBN (Print)978-1-5386-5519-1
DOIs
Publication statusPublished - 31 Dec 2018

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