Visible light communication and positioning using positioning cells and machine learning algorithms

被引：69

作者：

Chuang, Yu-Cheng ^{[1
]}

Li, Zhi-Qing ^{[1
]}

Hsu, Chin-Wei ^{[1
]}

Liu, Yang ^{[2
]}

Chow, Chi-Wai ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Coll Elect & Comp Engn, Dept Photon, Hsinchu 30010, Taiwan

[2] Philips Elect Ltd, Shatin, Hong Kong, Peoples R China

来源：

OPTICS EXPRESS | 2019年 / 27卷 / 11期

关键词：

Machine learning - Learning algorithms - Light;

D O I：

10.1364/OE.27.016377

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

We propose and experimentally demonstrate a practical visible light position (VLP) system using repeated unit cells and machine learning (ML) algorithms. ML is employed to increase the positioning accuracy. Algorithms of the 2nd-order regression ML model and the polynomial trilateral ML model are discussed. More than 80% of the measurement data have position error within 4 cm when using the 2nd-order regression ML model, while the position error is within 5 cm when using the polynomial trilateral ML model. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

引用

页码：16377 / 16383

页数：7

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