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

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 2 -order regression ML model and the polynomial trilateral ML model are dis...

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Veröffentlicht in:Optics express 2019-05, Vol.27 (11), p.16377-16383
Hauptverfasser: Chuang, Yu-Cheng, Li, Zhi-Qing, Hsu, Chin-Wei, Liu, Yang, Chow, Chi-Wai
Format: Artikel
Sprache:eng
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Zusammenfassung: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 2 -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 2 -order regression ML model, while the position error is within 5 cm when using the polynomial trilateral ML model.
ISSN:1094-4087
1094-4087
DOI:10.1364/OE.27.016377