Non-Line-of-Sight Error Reduction Algorithm for UWB Positioning

The emergence of ultra-wideband（UWB） has highly improved the indoor positioning performance of vehicles. However, UWB positioning technology is affected by Non-Line of Sight (NLoS) propagation of signals, which is one of key factors to affect vehicle positioning precision due to signal transmission path changed, resulting in a decrease in its positioning accuracy. In order to improve the performance of vehicle indoor positioning system based on UWB under non line of sight conditions, in this paper, an adaptive Kalman filtering algorithm with improved gain adjustment strategy is proposed to reduce NLoS errors, which has a stronger NLoS weakening effect. The method of dynamically adjusting the gain correction coefficient according to the current innovation size effectively solves the problem that a fixed and unchanging gain correction coefficient cannot adapt to different NLoS states. According to the experimental data, it can be seen that the root mean square error is reduced by 47.37%.