| With the new round of technological change,the global automotive industry is experiencing rapid development that has not been seen in a century,gradually transforming from a simple vehicle to a mobile intelligent terminal and basic unit of intelligent transportation.The expansion of indoor and outdoor vehicle positioning scenarios,as well as the improvement of positioning accuracy and reliability,have become a research hotspot for major automotive companies and scholars.In order to achieve continuous and accurate high-precision positioning of vehicles in complex urban environments,this thesis designs an indoor and outdoor combined positioning system based on GNSS/UWB and IMU.Through improving indoor and outdoor positioning technology and multi-source combined positioning algorithm,it achieves continuous and reliable high-precision positioning of vehicles in various urban scenarios.In this thesis,after receiving GNSS satellite signals in an outdoor scene without signal occlusion,RTK is used for high-precision outdoor positioning;The combination of GNSS and IMU is used in outdoor scenes with GNSS signal occlusion,and adaptive dynamic thresholds are implanted.From the perspective of acceleration and angular velocity,the dynamic filter switching between EKF and UKF is realized under different conditions,which improves the shortcomings of traditional single filter in combined positioning.At the same time,the improved GNSS/IMU combined positioning algorithm design for EKF and UKF is implemented to improve outdoor positioning accuracy and stability.Simulation experiments show that the improved filtered x-axis The positioning accuracy of y-axis and z-axis is improved by about 33% compared to that before filtering,with an average positioning error of 2.00cm;In indoor positioning scenarios,a combination of UWB and IMU is used to introduce a sparrow search algorithm and improve the search strategy to optimize the sparrow search algorithm.By optimizing the parameters of the UWB positioning algorithm,the convergence of UWB positioning is improved,and the positioning error of the system in non line-ofsight scenarios is reduced.The EKF parameters are improved through dynamic adjustment based on state error weights,and the combined UWB and IMU positioning algorithm design is implemented based on the improved EKF.Simulation experiments show that the improved positioning accuracy of x-axis and y-axis increases by 66.7%,and the average positioning error is within 2.00 cm.In the software and hardware design of the combined positioning system,this article adopts a modular design idea.The hardware platform architecture mainly includes four modules: data acquisition,central control processing,power management,and data transmission.The software uses hierarchical programming ideas and C++language to design the software in three parts: data acquisition and preprocessing,positioning algorithm design,and system integration and optimization.The core code for EKF and UKF algorithms is implemented,including state transition equations,observation equations,Kalman filter prediction,and update steps.Using the received signal strength to complete indoor and outdoor positioning identification and switching;Finally,three types of scene real vehicle tests are conducted.The experiment shows that in the urban multi lane scene without signal occlusion,the average positioning distance error is 1.50 cm;In the urban elevated or overpass scene,the average positioning distance error is 2.04 cm;In the urban tunnel and urban underground parking lot scenarios,the average error in the x direction of indoor UWB positioning coordinates is 4.40 cm,the average error in the y direction is 5.40 cm,the average distance error is5.78 cm,and the RMSE is 7.89 cm.The indoor and outdoor combined positioning system designed in this thesis can continuously output high-precision longitude and latitude coordinates,meeting the engineering positioning accuracy requirements. |
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