An Indoor Visible Light Positioning System Using Artificial Neural Network

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

doi:10.1109/ACP.2018.8596227

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 proceeding › Conference contribution › peer-review

27 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 language	English
Title of host publication	2018 Asia Communications and Photonics Conference (ACP)
Publisher	IEEE
ISBN (Electronic)	978-1-5386-6158-1
ISBN (Print)	978-1-5386-5519-1
DOIs	https://doi.org/10.1109/ACP.2018.8596227
Publication status	Published - 31 Dec 2018

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10.1109/ACP.2018.8596227

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title = "An Indoor Visible Light Positioning System Using Artificial Neural Network",

abstract = "We propose a visible light positioning system based on an artificial neural network (ANN) and optical camera communications. The receiver{\textquoteright}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.",

author = "Chun Lin and Bangjiang Lin and Xuan Tang and Zhenlei Zhou and Haiguang Zhang and Sushank Chaudhary and Zabih Ghassemlooy",

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T1 - An Indoor Visible Light Positioning System Using Artificial Neural Network

AU - Lin, Chun

AU - Lin, Bangjiang

AU - Tang, Xuan

AU - Zhou, Zhenlei

AU - Zhang, Haiguang

AU - Chaudhary, Sushank

AU - Ghassemlooy, Zabih

PY - 2018/12/31

Y1 - 2018/12/31

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85061441138

U2 - 10.1109/ACP.2018.8596227

DO - 10.1109/ACP.2018.8596227

M3 - Conference contribution

SN - 978-1-5386-5519-1

BT - 2018 Asia Communications and Photonics Conference (ACP)

PB - IEEE

ER -

An Indoor Visible Light Positioning System Using Artificial Neural Network

Abstract

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