Research On Key Technologies Of Joint Positioning Based On UWB And IMU

As enterprises continue to increase their demand for smart manufacturing upgrades,AGV is developing rapidly as one of the important components of smart manufacturing.Navigation and positioning,as one of the key technologies of AGV,are currently the focus of attention of relevant researchers.Ultra wide band(UWB)is gradually used in AGV navigation and positioning due to its good signal concealment and fast transmission rate.In order to meet the needs of AGV indoor navigation and positioning,this topic carries out the key technology research of UWB and Inertial Measurement Unit(IMU)joint positioning.The main research work is as follows:Research on UWB dynamic tracking method.In order to improve the problem of inaccurate dynamic tracking of UWB in non-line-of-sight indoors,a UWB-oriented dynamic target tracking method was proposed.Based on Kalman filter(KF),a noise reduction model was established,and the UWB ranging results were filtered and denoised.A particle filter was used to establish a UWB indoor dynamic target positioning and tracking model.The analysis results of tracking accuracy and tracking speed show that the method of dynamic target positioning and tracking is significantly better than the extended Kalman tracking method.The fusion algorithm of UWB and IMU was studied.In order to improve the positioning accuracy of the fusion positioning algorithm of UWB and IMU,a fusion positioning algorithm based on improved particle filtering was proposed.According to the theory of minimum variance estimation in adaptive optimal weighted fusion algorithm,a particle distribution weight adjustment strategy in particle filtering was given.In order to avoid divergence of the observation variance due to the actual environment,the threshold was used to limit the observation variance to the RMSE interval.Using the observation noise covariance and measurement values,the optimal weighting factors of each sensor were obtained to avoid the problem of algorithm divergence caused by weak or missing sensor signals.UWB and IMU fusion positioning experiment results show that the positioning accuracy of this method is significantly better than the extended Kalman fusion method.An experimental system based on UWB and IMU navigation was developed.Based on C# and Visual Studio 2012 software platform,the logistics truck UWB and IMU navigation experiment system was developed,and the proposed UWB and IMU fusion positioning algorithm was tested using this experiment system.The experimental system also provides a test platform for the laboratory to further carry out the research on UWB-based navigation and positioning methods.