Indoor high-accuracy multi-dimensional visible light positioning method with adaptive particle swarm optimization algorithm

. An indoor multi-dimensional visible light positioning method on the basis of visible light communication (VLC) has been proposed considering the impact of vertical and horizontal inclination angles of the target besides the traditional three-dimensional position parameters that can be expressed as (x,y,z) in the coordinate system. Specifically, the adaptive particle swarm optimization algorithm is adopted to search the global optimum in the whole space as the estimation position, which can efficiently improve searching ability and avoid premature convergence, thus efficiently improving the accuracy and stability of positioning results. Simulation results show that when the signal-to-noise ratio is equal to 25, 30, and 35 dB, over 91%, 93%, and 98% test points could achieve sub-centimeter level positioning, and similar to 94%, 90%, and 99% test points could satisfy the requirements of small angle in physics of horizontal inclination, respectively. And under such conditions, nearly all the test errors of vertical inclination are lower than 5 deg except one in 30 dB. Our work provides a good reference for the study of indoor VLC positioning method.