A UWB Location Algorithm---Based on Adaptive Kalman Filter

Abstract

Abstract In order to solve the problem of large fluctuations in UWB(Ultra Wide Band) positioning accuracy and solid-state deviations in the positioning results, which are in complex indoor environments, an adaptive Kalman filter method is introduced in the later stage of data processing. This method can better retain data information and obtain better filtering effects when the system noise is complex and measurement information is missing,.Thereby providing better positioning accuracy. The experiment uses AGV trolley equipped with UWB sensors to obtain measurement data, uses traditional Kalman filtering and adaptive Kalman filtering methods to compare the filtering effects of the algorithms. The experimental results show that when the measurement information is missing, compared with the traditional Kalman filter algorithm, the adaptive Kalman filter method is a real-time high-precision indoor positioning algorithm with higher positioning accuracy.