Abstract
Visible light radiated from light-emitting diodes is used to estimate the position of the receiver in a positioning system indoors. Wall reflection and noise are inevitable, which result in an error in the visible light indoor positioning system. Some indoor positioning algorithms based on fingerprint are compared through simulation. An improved indoor positioning algorithm of Bayesian theory is proposed. After using a Gaussian filter, several grid points that are close to each other are selected to be a cluster, and then the posterior probability of each cluster is calculated by the Bayesian algorithm. The cluster with the largest posterior probability is obtained to estimate the receiver’s position. The improved algorithm simplifies the Bayesian algorithm and improves the positioning accuracy, with an average error of 0.18 m.
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