Research On MEMS INS/GNSS Integrated Navigation System

The technological development of MEMS brings the innovation of inertial navigation equipment.The combination of satellite navigation and inertial navigation is one of the research hotspots and key navigations in the field of navigation.The positioning methods complement each other and,which increases the accuracy and stability of the navigation and positioning system.Based on this background,this paper studies and implements some key technologies of MEMS INS/GNSS integrated navigation and positioning system.The main work of this paper is as follows:(1)This paper describes the errors of MEMS inertial navigation equipment systematically,including deterministic errors and random errors.The compensation and calibration methods for deterministic errors are introduced.Six-position method was used to analyze the deterministic error of the accelerometer.Results show that the calibration method is simple and effective.In addition,the random errors of MEMS inertial navigation equipment are also analyzed and modeled.Allan variance analysis method is used to identify and fit the typical random errors of MEMS inertial navigation equipment,including zero-bias instability,angular random walk,and random rate walk.Etc.Aiming at the shortcomings of traditional Allan variance,dynamic Allan variance theory is applied to the random errors analysis of MEMS inertial navigation equipment.The time-varying characteristics of the random error of inertial navigation equipment are analyzed.The measured data is analyzed and verified by dynamic Allan analysis of variance.Results show that the time-varying characteristics of the experimental equipment are not obvious,indicating that the MEMS equipment has high stability.Based on the random error analysis,the method and strategy of modeling the random errors of inertial navigation equipment using stochastic differential equation modeling method are proposed.(2)According to the characteristics of MEMS inertial devices,methods for initial alignment of MEMS devices are summarized and analyzed,which include inertial system vector integral alignment algorithm,inertia-based Whaba optimal matrix solution alignment algorithm,and ratio-based kalman filtering algorithm for force measurement,kalman filter alignment algorithm based on velocity measurement,and the initial alignment algorithm for strapdown compass.The principle and steps of the above methods are introduced and discussed,the experimental verification and comparative analysis of each method are carried out.Also,the advantages and disadvantages of various alignment methods and their application strategies are pointed out.Aiming at the initial alignment of SINS under a large large misalignment angle,an initial alignment method for simplifying UKF filtering is proposed,and under various conditions(large misalignment angle,large azimuth misalignment angle,small misalignment angle,high and low precision inertial navigation equipment)was validated and analyzed for the proposed method.Results show that the proposed method is suitable for the initial alignment of high precision inertial navigation equipment under various misalignment angles.For low precision inertial navigation equipment,the horizontal alignment effect is better,bur the azimuth alignment convergence effect is not good,which needs further study.(3)The navigation algorithm of the strapdown inertial navigation system in the geocentric coordinate system and the local geographic coordinate system is deduced and mathematical model is established.The error equation of the inertial navigation algorithm is analyzed and modeled.The validity of the pure inertial navigation algorithm is analyzed,and the error propagation characteristics of the inertial navigation algorithm are also analyzed.(4)Based on the extended kalman filtering algorithm,the mathematical model of MEMS INS/GNSS loose and tight integrated navigation system is established,and the experimental analysis and validity verification of the two combined navigation models are carried out.The results show that the positioning of the integrated navigation system accuracy and stability have been significantly improved.In addition,the integrated navigation algorithm is applied to the actual use of vehicle AHRS and POS,and the forward and reverse filtering strategies are proposed for the post POS algorithm.The experimental results show that the algorithm is effective.