Study On The Application Of Based On Unscented Kalman Filter Of SINS/GPS Tight Coupling Integrated Navigation System

Due to the continuous progress of the times,especially with the advent of 5G communication technology,the new generation of Unmanned Driving Technology(UDT)will release great vitality,and navigation and positioning technology has become a hot issue in the field of UDT.In order to achieve higher precision of the navigation and positioning of UDT,this thesis focuses on the SINS/GPS tight coupling integrated navigation system based on Adaptive Unscented Kalman Filter(AUKF).For the sake of avoiding a single navigation system cannot achieve high navigation accuracy in a complex navigation environment,the Strap-down Inertial Navigation System(SINS),which is assisted by the GPS global positioning system,the navigation information of both are filtered and blended by Kalman Filter.Firstly,the structure of each navigation subsystem is introduced.The initial alignment of SINS static base and the pseudo-range positioning method of GPS are studied.By determining the initial value of the attitude matrix of the SINS system,the quaternion method is used to solve the mechanical programming equation of SINS to obtain the initial value of the platform error angle,and the information of velocity and position.Considering of two situations,the first one is that the estimation error of Kalman Filter(KF)will be accumulated over time even leads to filter divergence,and the another is the position-based and velocity-based Loosely Coupling scheme have lower filtering precision.This thesis designs a SINS/GPS tight integrated navigation system based on Pseudo-range and Pseudo-range rate.Firstly,the sources of the error of SINS and GPS is analyzed,and the mathematical models of SINS and GPS are established respectively.Then the state equation and the measurement equation of the navigation subsystem are merged into the state equation and the measurement equation of the tight coupling integrated navigation system based on the Pseudo-range and the Pseudo-range rate.And complete the discretization.Because of the error model for integrated navigation system is generally nonlinear,in order to meet the demands of practical appliance,in this thesis,the working principle and filtering process of nonlinear extended Kalman filter(EKF)are briefly introduced.Due to application limitations of EKF,based on Unscented Transformation(UT)and Minimum Slope Simplex ? Point Set Sampling Strategies Unscented Kalman Filter(UKF)are studied.Secondly,in order to improve the sampling accuracy of the minimum slope single-shape ? point set sampling strategy,an adaptive UKF(AUKF)based on proportional adjustment factor is designed.The simulation results show that for the SINS/GPS Tight Coupling Integrated Navigation System,the AUKF which is based on the proportional adjustment factor,can not only avoiding the influence of non-local effects and improving the filtering accuracy,but also get better control performance,tracking and fault tolerance.On the other hand,the error output curve of AUKF is smoother than the error output curve based on the UT transformation.