Research On Indoor Location Algorithm Based On UWB/IMU Fusion

With the rise of the Internet of Things and smart city,indoor positioning technology and its application are becoming increasingly important in people's life.Ultra-wide Band(UWB)positioning technology and Inertial Measurement Unit(IMU)positioning technology have significant advantages in indoor positioning due to their high positioning accuracy and free from environmental influence.Because of the limitations of single positioning technology,the combined positioning technology of UWB and IMU has become a hot indoor positioning solution.Therefore,in this paper,UWB positioning technology and IMU positioning technology are studied,and the combination of the two positioning,so as to provide a solution to meet the positioning needs of complex indoor environment.The main work of this paper is as follows:Firstly,to solve the problem that UWB positioning system is greatly affected by non-line-of-sight(NLOS)error,and IMU positioning system is greatly affected by cumulative error,which leads to low positioning accuracy Of the loosely-coupled positioning algorithm,an improved loosely-coupled positioning algorithm is proposed.Firstly,NLOS propagation was identified by differential barometer height measurement method,and the influence of NLOS error on UWB location was reduced by weighted least square method.Then,the cumulative error decision threshold of IMU was introduced into the fusion algorithm to identify the positioning effect of UWB and IMU at the current sampling point,so as to reduce the impact of cumulative error on IMU positioning results,and achieve the purpose of improving the positioning accuracy of loosely-coupled.Then,an improved tightly-coupled positioning algorithm is proposed to solve the problem that the performance of the loosely-coupled positioning system is poor or even unable to work when the number of UWB base stations is less than four.Firstly,the UWB rangefinder is detected by threshold judgment,and then replaces it by IMU measurement information.Then the federated extended Kalman filter algorithm is used to fuse the UWB ranging values and the IMU positioning results to achieve the purpose of improving the positioning accuracy of tightly-coupled.Finally,UWB and innovative marketing system in an indoor simulation in the complex environment based on the measured data,the experimental results verified the improved loosely-coupled localization algorithm on the positioning accuracy than traditional combination algorithm is improved by 45.71%,improve the tightly-coupled of localization algorithm can also be than traditional tightly-coupled localization algorithm has higher positioning accuracy.