Research On Vehicle Integrated Model Based On MEMS-INS/CNSS

In recent years,the Integrated vehicle navigation system based on MEMS-INS/GNSS(MEMS,Micro-Electro-Mechanical System;INS,Inertial Navigation System;GNSS,Global Navigation Satellite System)System has been widely used.But at the same time,there is the problem of low cost MEMS-INS precision error need to be calibrated,in addition,there is also the problem of attitude measurement and navigation and positioning accuracy limitation when the satellite is seriously covered and completely unlocked.In this paper,several key issues are explored in depth.The main research contents and results include:1.Aiming at the existence of accelerometer and gyroscope inertial sensor zero bias,sensitivity and skew error,multi position rotating field calibration method is proposed in this paper,the method can realize the three-axis accelerometer,the triaxial gyro calibration.As for magnetometers' error above,this article put forward by ellipsoid fitting model,three axis magnetometer can be calibrated through the model.The static navigation accuracy is improved after calibration,which verifies the validity of the multi-position rotation field calibration method.The validity of ellipsoid fitting method is verified by comparing the magnetometer data after calibration with the local magnetic induction intensity.2.In view of the problem that the attitude measurement system is subject to the harmful acceleration of the carrier and the influence of the surrounding magnetic field during the attitude measurement,this paper studies how to use the algorithm to effectively resist the interference from these two aspects.Firstly,this parper study the traditional navigation position reference system based on EKF attitude measuring conditions,and then this paper design the adaptive EKF to judging the accelerometer and magnetometer sensor signal,when the signal is above a certain threshold,the system will eliminate harmful information,in this way,we can curbing the sudden acceleration interference and magnetic interference.Linear acceleration and magnetic interference are added to the dynamic vehicle experiment data to verify the effectiveness of the adaptive ekf-based AHRS anti-interference model in resisting external acceleration and magnetic interference.At the same time,in the case of satellite overshadowing and complete loss of lock,with the loss of GNSS assist,results in the attitude drift and the failure of normal navigation of inertial navigation.Because the AHRS system does not need GNSS assist to accurately measure the attitude,the navigation accuracy and navigation performance can be improved.3.Finally,in order to deal with the problem of interference on the navigation effect of MEMS-INS/GNSS integrated navigation system in the covered environment,this paper proposed Evolutionary Mind Algorithm(MEA)to optimize the Back propagation(BP)neural network Algorithm(MEA-BP)aided MEMS-INS/GNSS navigation model.When the number of satellite is nomal,neural network algorithm use the position and time as training data to establish the model,when the number of satellite reduce,we can still using the prediction of the the model that neural network trained before to assist MEMS INS/GNSS navigation,and when no satellites to use,we will use the prediction of the model of the neural network trained before to assist INS navigation.The effectiveness of MEA-BP assist MEMS-GNSS/INS system under the condition of less satellite and no satellite was verified by manually setting multiple cover intervals and interrupt intervals in the measured vehicle data,and its navigation accuracy was greatly improved.