Research On UWB-based Real-time 3D Target Positioning System

With the development of information technology,the commercialization of positioning services has a broad prospect.UWB uses narrow pulses to transmit data,and has outstanding anti-multipath performance,which is widely used in the field of positioning.Intelligent transportation tools such as drones and unmanned vehicles require precise positioning services.To ensure safety,the stability,accuracy,and real-time efficiency of the positioning system is the top priority of the research.For RTK technology with a plane accuracy of up to10 cm,its ambiguity resolution takes a long time,and conditions such as initialization and disconnection will inevitably cause great security risks.Therefore,this system is based on UWB technology and uses a nonlinear filtering positioning algorithm to provide a high-stability,high-real-time,and high-precision positioning service for the flight tag,so as to replace or assist RTK,and even provide a reference for 3D real-time positioning in other scenes.The main contents of this paper are as follows:(1)This article studies the principles of UWB and the characteristics of ranging technology,analyzes multiple communication modes based on TOA ranging methods,and tests the number of messages and ranging duration required by different base stations.In order to improve the real-time performance of the multi-base station system and reduce the ranging time and system energy consumption,DS-TWR is optimized using the idea of message multiplexing.(2)In this paper,TOA is used to explore the influence of antenna,temperature,occlusion and other factors on the UWB ranging performance in the experiment,and to study the corresponding temperature compensation and antenna calibration methods.(3)This paper conducts mathematical modeling of the positioning system.In order to improve the positioning accuracy and simplify the deployment of base stations,the three-dimensional positioning algorithm is disassembled and optimized,and the improved positioning algorithm is tested through a simple LMS to determine the framework for subsequent algorithm discussions.(4)Based on the improved positioning algorithm framework,the principle characteristics of the nonlinear filtering algorithm PF and the nonlinear Gaussian filtering algorithm EKF,UKF,CKF are studied and analyzed,and the simulation program is written by combining these algorithms with the mathematical model of the positioning system.A comprehensive analysis of their stability,real-time performance,and accuracy was carried out in three cases,and finally the CKF-PF combined positioning scheme was determined.(5)The upper computer and lower computer software are designed for this system,and an experiment platform is built to test the positioning performance of the system in multiple positioning scenarios.In low-altitude fixed-point positioning,the minimum error can reach5cm;when the UAV is in flight positioning and tracking,it takes less than 0.5s to initialize the system to the position convergence;in the landing positioning of the UAV,the minimum error is close to 5cm,and the maximum error is not Over 31 cm.