Research on TOF⁃Based UWB Indoor Positioning Technology and Fusion Algorithms

Aiming at the problems of low positioning accuracy and poor stability in multi⁃effect and non⁃line⁃of⁃sight conditions, a new indoor positioning system Chan⁃Taylor⁃Unscented Kalman Filter (C⁃T⁃UKF) combined positioning algorithm is designed based on the time of flight positioning algorithm, combined with the Chan⁃Taylor (C⁃T) cooperative positioning algorithm, and fused with the Unscented Kalman Filter (UKF) algorithm. The system mainly consists of positioning base stations, positioning tags, wireless communication systems and upper computers, etc. The Chan algorithm is adopted to calculate the distance measured by the time of flight method, and the calculated coordinates are used as the initial value of the Taylor algorithm for iterative calculation. The iterative results are smoothed by the Unscented Kalman algorithm. The results show that the positioning system based on this algorithm has the characteristics of high accuracy, strong stability and low cost. The average positioning errors in line⁃of⁃sight and non⁃line⁃of⁃sight conditions are less than 0.17 m and 0.20 m respectively, and it can be applied to high⁃precision positioning scenarios.