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 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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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. |
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ISSN: | 1094-4087 1094-4087 |
DOI: | 10.1364/OE.27.016377 |