An UWB/PDR Fusion Algorithm Based on Improved Square Root Unscented Kalman Filter

How to improve the accuracy of indoor positioning is a hot issue in the research of wireless indoor positioning technology. In order to solve the problem that Ultra Wideband (UWB) technology cannot locate accurately under the condition of non-line of sight (NLOS), this paper proposes an indoor positioning method combining UWB and Pedestrian Dead Reckoning (PDR).The method utilizes the advantages of high frequency noise characteristics of PDR to suppress the NLOS error generated by UWB. Furthermore, in order to get better integration of UWB and PDR, an improved square root unscented Kalman filter (ISR-UKF) is proposed. The simulation results show that the improved algorithm proposed in this paper can effectively improve the indoor positioning accuracy, and ensure the stability and continuity of the positioning system.