Design And Research Of Positioning System Based On UWB

In recent years,the location service industry has developed drastically.Because of the requirement of Internet of Things service,intelligent city construction,disaster relief and disaster fighting,location information service has also attracted more and more attention.Global positioning system(GPS)and Beidou positioning system cover outdoor location information services,but cannot be effectively applied to indoor environment,so different kinds of indoor positioning schemes are also bred out.Among them,the indoor positioning system based on Ultra Wideband(UWB)technology has attracted the attention of most researchers because of its characteristic of high positioning accuracy,strong penetration and low power consumption.Aiming at the current research status of UWB positioning system and the obstacles that need to be solved in the future,this paper makes the following contributions:1.The indoor positioning system based on UWB technology is designed.The hardware is based on DW1000 RF chip and controlled by STM32 single chip computer.The upper computer software is developed on C#.NET platform.On this basis,this paper intensive studies the Time of Arrival(TOA)and Time Difference of Arrival(TDOA)positioning methods based on UWB signal indoor positioning.2.Aiming at the characteristics of TOA and TDOA positioning methods,the positioning accuracy depends mostly on the time synchronization accuracy between base stations.Based on the Two-Way Ranging(TWR)method and the Symmetric Double-Sided Two-Way Ranging(SDSTWR)method,a time synchronization mode based on time difference extraction is proposed,which reduces the process of time synchronization,shortens the time synchronization delay and improves the performance of time synchronization between base stations to a great extent.Thus,the positioning performance of the system is improved.3.As for the traditional Kalman filtering algorithm used in UWB location algorithm,the prior knowledge such as covariance coefficient needed for filtering is difficult to obtain accurately.In the process of system operation,the traditional Kalman filter cannot effectively deal with the disturbance caused by environment and the change of measurement value when the temperature drift of measurement results occurs due to the change of environment factor or the long-term operation of base station.Therefore,this paper proposes an adaptive Kalman filtering algorithm,which can estimate the measurement error and process error automatically according to the historical value and update automatically.The system is tested at the last of the paper.The test results indicate that the location algorithm mixed with the adaptive Kalman filter and the time synchronization method of time difference extraction can increase the location stability in static positioning and improve the positioning accuracy in dynamic positioning.The positioning accuracy of the system reaches less than 10 cm,which lays a good foundation for practical application.