Research on Indoor Combination Positioning Algorithm Based on UWB

To address the issue of decreased positioning accuracy and stability in indoor positioning algorithms based on UWB technology due to non-line-of-sight (NLOS) errors during ranging, an improved Chan-Taylor-Kalman filter fusion positioning algorithm is proposed in the paper. This algorithm is capable of detecting NLOS environments and mitigating certain NLOS errors. Initially, the algorithm estimates the target node's position using the Chan algorithm and calculates the difference between the TDOA value and the initial TDOA value. It then assesses the presence of NLOS errors and corrects the TDOA values in cases of NLOS errors. These corrected TDOA values are subsequently introduced into the subsequent algorithms. Weighting factors are introduced to perform a mixed weighting of the Chan and Taylor algorithms to reduce system noise errors. Finally, Kalman filtering is applied to further reduce system noise errors and NLOS errors, thereby enhancing positioning accuracy. Simulation results indicate that the algorithm presented in the paper demonstrates good positioning accuracy performance in both line-of-sight (LOS) and NLOS environments.