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Real-time High-precision Two-dimensional Positioning Technology For Multi-athletes Based On UWB

Posted on:2022-11-17Degree:MasterType:Thesis
Country:ChinaCandidate:Y X HanFull Text:PDF
GTID:2518306761490194Subject:Automation Technology
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In recent years,emerging concepts such as "smart sports" and "technological sports" have been gradually applied to the field of sports health to preferably analyze the sports conditions of athletes.Because Ultra-Wideband(UWB)technology has the characteristics of high-speed data transmission,high ranging accuracy,and strong anti-interference,the application of UWB technology to sports training can realize the real-time monitoring of two-dimensional position trajectories of multiple athletes.However,in the process of site construction,it is inconvenient to obtain the coordinates of the base stations.In addition,due to the problem of clock drift in the positioning system,there is an error in the time difference when the positioning system applies the Time Difference of Arrive(TDOA)positioning method.Aiming at the problem of inconvenience in obtaining the location of UWB base stations in sports fields,a fast self-localization method for UWB mobile base stations based on Time of Flight(TOF)is proposed.First,determine the local coordinate system according to the base station layout,establish the coordinate equation of each base station based on the mutual ranging information between UWB base stations,then use the Least Square method to calculate the coordinates of each base station,and finally,DOP is used to evaluate the layout scheme of the base station in the sports field.The experimental results show that the average positioning accuracy of the mobile base station is within 0.05 m.Compared with traditional manual measurement methods,base station self-positioning can effectively save the deployment time of base stations and reduce the workload.Aiming at the problem of clock drift in the positioning system,an error compensation algorithm based on KF is proposed in this paper.Firstly,the relationship between the clock offset and the timestamps received by the slave base station is analyzed through the relationship between the sending and receiving timestamps between the master base station and the slave base station in the same clock cycle.After that,in order to improve the accuracy of the algorithm,a synchronization error compensation method based on the Kalman filter algorithm is designed.It is verified by experiments that the error compensation algorithm can effectively reduce the clock error between the master base station and the slave base station.Aiming at the demands of real-time high-precision positioning of multiple athletes in complex environments,this paper adopts the TDOA method and the Taylor algorithm to solve the position of the tag to be located.Then,a two-dimensional positioning error compensation method based on the EKF algorithm is proposed.It has been verified by the sports field test that the positioning accuracy of the athletes is within 24 cm,which meets the positioning accuracy requirements of the personnel in the sports field.Based on UWB technology,this paper builds a wireless real-time system and proposes a technology suitable for real-time high-precision two-dimensional positioning of multiple athletes in the sports field.At present,the algorithm is applied in football training events,which can break through key technologies such as the accurate acquisition of athletes' positions,micro-integration of wearable devices,test data processing,and visualization.The system provides reliable and effective data support for athletes' training effect evaluation and competition tactical level in the training process.In addition,the positioning system in this paper has the characteristics of portable equipment,low power consumption,and high precision,which provides a solution for obtaining multi-person location information for navigation and positioning in the indoor environment.
Keywords/Search Tags:UWB, TODA, multi-person positioning, base station self-positioning, clock synchronization, Kalman filter
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