An Improved Indoor 3-D Ultrawideband Positioning Method by Particle Swarm Optimization Algorithm

Ultra-wideband (UWB) technology is the potential indoor positioning method, which is based on the time of arrival (TOA) principle and Kalman filter (KF) algorithm. In this research, a high-precision positioning method is developed by the modified particle swarm optimization (PSO) algorithm to improve the indoor 3-dimensional (3D) positioning accuracy. The modified PSO algorithm is utilized to determine the optimal parameters of KF algorithm according to the pre-positioned correction points. In addition, the effects of the number of pre-positioned correction points on the positioning accuracy are systematically investigated, and the positioning accuracy is the highest when the number of pre-positioned correction points is 8. The experimental results show that the root mean square error (RMSE) and mean absolute error (MAE) of the traditional positioning method are 21.28 and 9.96 cm, while those of the developed method are 19.02 and 8.45 cm. Therefore, the positioning accuracy can be improved by the developed method, it has great potential in the high-accuracy positioning for the complex indoor environment.