Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Using Received-Signal-Strength (RSS) Pre-Processing and Convolutional Neural Network (CNN) to Enhance Position Accuracy in Visible Light Positioning (VLP)

Not Accessible

Your library or personal account may give you access

Abstract

We propose and demonstrate a received-signal-strength (RSS) pre-processing scheme to mitigate light-deficient-region occurred in visible-light-positioning (VLP) and convolutional-neural-network (CNN) to enhance VLP performance. The RSS pre-processing and CNN model are discussed.

© 2022 The Author(s)

PDF Article  |   Presentation Video
More Like This
3-Dimensional Visible Light Positioning (VLP) Using Two-Stage Neural Network (TSNN) and Signal-Strength-Enhancement (SSE) to Mitigate Light Non-Overlapping Regions

Li-Sheng Hsu, Chi-Wai Chow, Yang Liu, Yun-Han Chang, Deng-Cheng Tsai, Tun-Yao Hung, Yuan-Zeng Lin, Yin-He Jian, and Chien-Hung Yeh
Tu5.52 European Conference and Exhibition on Optical Communication (ECOC) 2022

Using DIALux and Regression-based Machine Learning Algorithm for Designing Indoor Visible Light Positioning (VLP) and Reducing Training Data Collection

Shao-Hua Song, Dong-Chang Lin, Yun-Han Chang, Yun-Shen Lin, Chi-Wai Chow, Yang Liu, Chien-Hung Yeh, Kun-Hsien Lin, Yi-Chang Wang, and Yi-Yuan Chen
Tu5E.3 Optical Fiber Communication Conference (OFC) 2021

High Accuracy Robot Indoor Navigation Using Visible Light Positioning and LiDAR Fusion

Wanlin Liang, Shangsheng Wen, Linyi Huang, and Weipeng Guan
JW3B.8 CLEO: Applications and Technology (CLEO:A&T) 2022

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads


More Like This
3-Dimensional Visible Light Positioning (VLP) Using Two-Stage Neural Network (TSNN) and Signal-Strength-Enhancement (SSE) to Mitigate Light Non-Overlapping Regions

Li-Sheng Hsu, Chi-Wai Chow, Yang Liu, Yun-Han Chang, Deng-Cheng Tsai, Tun-Yao Hung, Yuan-Zeng Lin, Yin-He Jian, and Chien-Hung Yeh
Tu5.52 European Conference and Exhibition on Optical Communication (ECOC) 2022

Using DIALux and Regression-based Machine Learning Algorithm for Designing Indoor Visible Light Positioning (VLP) and Reducing Training Data Collection

Shao-Hua Song, Dong-Chang Lin, Yun-Han Chang, Yun-Shen Lin, Chi-Wai Chow, Yang Liu, Chien-Hung Yeh, Kun-Hsien Lin, Yi-Chang Wang, and Yi-Yuan Chen
Tu5E.3 Optical Fiber Communication Conference (OFC) 2021

High Accuracy Robot Indoor Navigation Using Visible Light Positioning and LiDAR Fusion

Wanlin Liang, Shangsheng Wen, Linyi Huang, and Weipeng Guan
JW3B.8 CLEO: Applications and Technology (CLEO:A&T) 2022

Computationally Efficient Pre-Distortion based on Adaptive Partitioning Neural Network in Underwater Visible Light Communication

Hui Chen, Wenqing Niu, Guoqiang Li, Zhixue He, Junwen Zhang, Nan Chi, and Ziwei Li
W3I.3 Optical Fiber Communication Conference (OFC) 2022

Data-Efficient Artificial Neural Networks with Gaussian Process Regression for 3D Visible Light Positioning

Weikang Zeng, Huayang Chen, Jiajia Chen, and Xuezhi Hong
Tu5E.7 Optical Fiber Communication Conference (OFC) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.