Study on the improved unscented Kalman filter ultra-wideband indoor location algorithm based on two-way time-of-flight

Abstract

Traditional indoor location technologies based on wireless sensor network have difficulty in satisfying the requirements of positioning accuracy and real-time tracking in the non-line-of-sight (NLOS) environment due to considerable errors. In this study, an indoor location and tracking algorithm for the ultra-wideband (UWB) system was proposed to solve accurate location and tracking problems of the moving target in the complicated indoor environments. First, this algorithm measured the distance between tag and anchor accurately by the two-way time-of-flight (TW-TOF) method, and then calculated the position coordinates of the tag by the CHAN algorithm after the range measurement. Second, the coordinates of tag position were used as the observation value of unscented Kalman filter (UKF) with the state updating equation of UKF modified. Finally, the real-time position states and speed of the tag could be acquired. The proposed algorithm was compared with the extended Kalman filter (EKF) through a simulation experiment. Results demonstrate that the improve UKF algorithm can realize accurate location and dynamic tracking of the moving target in the indoor NLOS environment. The location accuracy of the proposed algorithm is 33.5% higher than that of the EKF algorithm. The study can provide certain references for accurate location and tracking of the moving target in the complicated indoor environments.