K-Means-Based DNN Algorithm for a High Accuracy VLP System

Jianli Jin; Shouwei Wang; Lu Yang; Huimin Lu; Jianping Wang; Danyang Chen; Lifang Feng; Hongyao Chen; Hongyu Zhang

doi:10.3390/photonics11030209

Photonics (Feb 2024)

K-Means-Based DNN Algorithm for a High Accuracy VLP System

Jianli Jin,
Shouwei Wang,
Lu Yang,
Huimin Lu,
Jianping Wang,
Danyang Chen,
Lifang Feng,
Hongyao Chen,
Hongyu Zhang

Affiliations

Jianli Jin: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Shouwei Wang: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Lu Yang: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Huimin Lu: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Jianping Wang: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Danyang Chen: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Lifang Feng: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Hongyao Chen: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Hongyu Zhang: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China

DOI: https://doi.org/10.3390/photonics11030209
Journal volume & issue: Vol. 11, no. 3
p. 209

Abstract

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In this paper, a positioning algorithm based on the combination of K-means clustering and deep neural networks (DNNs) is first presented for multiple light emitting diodes (LEDs) integrated with visible light positioning (VLP) systems. We extracted the maximum value from the collected optical power of LEDs, utilizing the ratio of each optical power to this maximum optical power as the input training data. The experimental results demonstrate that the proposed algorithm outperformed the conventional DNN algorithm in terms of anti-jamming capability and positioning accuracy. In addition, the positioning accuracy of the proposed system reached a millimeter level, which is the highest experimental VLP accuracy, to the best of our knowledge.

Published in Photonics

ISSN: 2304-6732 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Engineering (General). Civil engineering (General): Applied optics. Photonics
Website: http://www.mdpi.com/journal/photonics

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