Design of High Precision Positioning System for Indoor Visible Light Communication

XU Yi-qin; CHEN Zhi-tao; YUAN Tao; CHEN Hao; GU Zhi-liang; ZHANG Zhi-qing; ZHANG Qiang; XU

doi:10.3788/fgxb20194001.0106

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Design of High Precision Positioning System for Indoor Visible Light Communication

Luminescence Applications and Interdisciplinary Fields | 更新时间：2020-08-12

- Design of High Precision Positioning System for Indoor Visible Light Communication
- Chinese Journal of Luminescence Vol. 40, Issue 1, Pages: 106-114(2019)
- 作者机构：
  
  1. 华南师范大学物理与电信工程学院,广东广州,510006
  2. 广东省半导体产业技术研究院,广东广州,510650
  3. 华南理工大学,广东广州,510650
- 作者简介：
- 基金信息：
  
  Supported by National Natural Science Foundation of China(11304048);Science and Te
- DOI：10.3788/fgxb20194001.0106
  CLC： TN911.33;TN912.11
- Received：10 April 2018，
  
  Revised：04 July 2018，
  
  Published Online：06 July 2018，
  
  Published：05 January 2019
- 稿件说明：
移动端阅览
许毅钦, 陈志涛, 袁涛等. 室内可见光通信高精度定位系统设计[J]. 发光学报, 2019,40(1): 106-114

XU Yi-qin, CHEN Zhi-tao, YUAN Tao etc. Design of High Precision Positioning System for Indoor Visible Light Communication[J]. Chinese Journal of Luminescence, 2019,40(1): 106-114
许毅钦, 陈志涛, 袁涛等. 室内可见光通信高精度定位系统设计[J]. 发光学报, 2019,40(1): 106-114 DOI： 10.3788/fgxb20194001.0106.

XU Yi-qin, CHEN Zhi-tao, YUAN Tao etc. Design of High Precision Positioning System for Indoor Visible Light Communication[J]. Chinese Journal of Luminescence, 2019,40(1): 106-114 DOI： 10.3788/fgxb20194001.0106.

摘要

基于接收信号强度算法的可见光室内定位系统具有结构简单的特点，但是由于漫反射信道、系统噪声等因素，其定位精度受到很大限制，为此提出使用人工神经网络对室内可见光信道参数进行学习，拟合室内信道参数的真实值，实现高精度定位。首先，使用CDMA调制技术消除室内可见多参考点光通信带来的码间干扰问题，CDMA解扩信号经过归一化操作后输入人工神经网络对坐标函数进行训练，使之拟合室内可见光通信信道参数，估计出接收机到各个LED参考点之间的空间距离。其次，由于神经网络训练数据噪声及接收机信号噪声会影响定位精度，我们提出使用Newton-Raphson迭代法，进一步逼近测试点的真实坐标。实验结果表明，在1 m1 m1.2 m的室内可见光通信定位系统模型中，本系统在二维定位应用时平均定位误差为0.87 cm；在三维定位应用时平均定位误差为1.47 cm。本文提出的基于接收信号强度的可见光室内定位系统，使用CDMA调制技术，接收信号经过解扩后输入人工神经网络对信道参数进行距离估计，为了进一步地减小噪声等随机过程带来的定位误差，提出一种定位专用的定位坐标解迭代逼近算法，结果表明本系统在二维定位及三维定位均可实现很高的定位精度。

Abstract

The visible light indoor positioning system based on the received signal strength algorithm has a simple structure. However

due to diffuse reflection channels

system noise and other factors

the positioning accuracy is greatly limited. Therefore

this paper proposes to use artificial neural network to learn indoor visible light channel parameters

and to fit the real value of indoor channel parameters as well as achieve high-precision positioning. Firstly

the CDMA modulation technique is used to eliminate the problem of inter-symbol interference caused by visible multi-reference optical communications in the room. Then the CDMA despreading signal is normalized and input to an artificial neural network to train the coordinate function so as to fit the indoor visible light communication channel parameters. Finally

the spatial distance between the receiver and each LED reference point is estimated. Besides

because the neural network training data noise and the receiver signal noise will affect the positioning accuracy

the Newton-Raphson iterative method is used to further approximate the true coordinates of the test points. The experimental results show that in the 1 m1 m1.2 m indoor visible light communication positioning system model

the average positioning error of this system in the two-dimensional positioning application is 0.87 cm; in the three-dimensional positioning application

the average positioning error is 1.47 cm. In this paper

a visible light indoor positioning system based on received signal strength is proposed. This system uses CDMA modulation technology. The received signal is despreaded and input artificial neural network to estimate the channel parameters. To further reduce the positioning error caused by random processes such as noise

an iterative approximation algorithm for positioning-based coordinate solutions is proposed. The results show that the system can achieve high positioning accuracy in both two-dimensional positioning and three-dimensional positioning.

关键词

Keywords

references

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Related Institution

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