Experimental demonstration of an indoor positioning system based on artificial neural network

Bangjiang Lin; Qingyang Guo; Chun Lin; Xuan Tang; Zhenlei Zhou; Zabih Ghassemlooy

doi:10.1117/1.OE.58.1.016104

Experimental demonstration of an indoor positioning system based on artificial neural network

Bangjiang Lin, Qingyang Guo, Chun Lin, Xuan Tang, Zhenlei Zhou, Zabih Ghassemlooy

Mathematics, Physics and Electrical Engineering

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

We propose a 2-D visible light positioning system based on the artificial neural network (ANN), where the light-emitting diodes are grouped into blocks and the block coordinates are encoded with under-sampled modulation. A camera is used to decode the block coordinate in the receiver. The receiver’s position is approximately and precisely estimated using 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.

Original language	English
Article number	016104
Journal	Optical Engineering
Volume	58
Issue number	01
DOIs	https://doi.org/10.1117/1.OE.58.1.016104
Publication status	Published - 8 Jan 2019

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title = "Experimental demonstration of an indoor positioning system based on artificial neural network",

abstract = "We propose a 2-D visible light positioning system based on the artificial neural network (ANN), where the light-emitting diodes are grouped into blocks and the block coordinates are encoded with under-sampled modulation. A camera is used to decode the block coordinate in the receiver. The receiver{\textquoteright}s position is approximately and precisely estimated using 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.",

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AU - Lin, Bangjiang

AU - Guo, Qingyang

AU - Lin, Chun

AU - Tang, Xuan

AU - Zhou, Zhenlei

AU - Ghassemlooy, Zabih

PY - 2019/1/8

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AB - We propose a 2-D visible light positioning system based on the artificial neural network (ANN), where the light-emitting diodes are grouped into blocks and the block coordinates are encoded with under-sampled modulation. A camera is used to decode the block coordinate in the receiver. The receiver’s position is approximately and precisely estimated using 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.

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