UWB Localization Algorithm Based on Kalman Filter and IPSO Algorithm
Yiran Hu, Xu Zhao · 2024
Aiming at the problem that Ultra Wide Band (UWB)devices are susceptible to environmental interference and localization errors, this paper firstly uses Kalman filter to process the ranging values to eliminate the erroneous ranging values caused by noise interference in the environment, and then uses Gaussian filter to process the ranging values to improve the ranging accuracy, and then solves the initial coordinates by Chan algorithm, and then uses the coordinates as the initial value of searching in the improved particle swarm algorithm to further solve the more accurate coordinate values, and measures the positioning accuracy by the mean square error (RMSE) of the algorithm. The coordinates are then used as the search initial values for the improved particle swarm algorithm, which is further solved to obtain more accurate coordinate values, and the localization accuracy of the algorithm is measured by the mean square error (RMSE). Through the experiments, the range error of this algorithm in the presence of signal interference is reduced by 63.4% compared with Chan algorithm, 26.7% compared with Chan-Kalman algorithm, and its range error is in the centimeter level, which can be concluded that this algorithm can effectively solve the problem of improving the accuracy of UWB indoor positioning in the presence of interference.