Author:
Cheng Yue,Shao Jianhua,Wu Ruiqi
Abstract
Abstract
A compressive sensing optimization algorithm for indoor three-dimensional (3D) positioning based on visible light was proposed in this paper. This is the first work that applies compressive sensing to indoor 3D positioning. The solution of the fingerprint’s weight was transformed into a compressive sensing reconstruction, the coordinates of the point to be positioned are obtained by reconstruction using the KNN algorithm and the grey wolf optimization (GWO) algorithm. The self-exploration GWO (SEGWO) algorithm was proposed by introducing a self-exploration mechanism into GWO to improve the convergence performance of the algorithm. The localization error of the proposed method in 3D space is 5.79cm, which is significantly lower than other similar algorithms.
Subject
Computer Science Applications,History,Education
Reference14 articles.
1. A survey of positioning systems using visible LED lights;Zhuang;IEEE Communications Surveys & Tutorials,2018
2. The research of indoor positioning based on visible light communication;Wang;China Communications,2015
3. Visible Light Positioning Algorithm Based on Particle Swarm Optimization Compressive Sensing;Xu;Chinese Journal of Lasers,2021
4. An Accurate Visible Light Positioning System Using Regenerated Fingerprint Database Based on Calibrated Propagation Model;Alam;IEEE Transactions on Instrumentation and Measurement,2019