Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm
Zhenyu Wang, Zhonghua Liang, Xunuo Li, Hui Li
Abstract
In this paper, an improved particle swarm optimization (IPSO) algorithm is proposed to solve the problem of premature convergence and redundant particles of the original particle swarm optimization (PSO) used in visible light positioning (VLP) systems. In the proposed IPSO algorithm, an adaptive particle initialization method based on Min-Max algorithm is used to adjust the number of particles and ensure that there are always particles near the target node (TN). Moreover, a nonlinear decreasing strategy of inertia weight is designed to ensure the stability of particle velocity during the iterative process. Simulation results show that, compared with the original PSO algorithm, the averaged positioning accuracy of the proposed IPSO-Min-Max algorithm is enhanced significantly at the expense of limited time consumption. What’s more, we also find that for the proposed IPSO-Min-Max algorithm the increase of particle generation spacing will reduce the positioning delay but with the penalty in positioning accuracy. Therefore, it is necessary to select an appropriate particle spacing value according to specific requirements.