The Implementation Of Position And Attitu De Based On Low-cost MEMS AHRS And MEMS/GNSS

In recent years,the market for azimuth reference systems at home and abroad has become increasingly mature.The output stability and accuracy of the Attitude and Heading Reference System(AHRS)directly affect the attitude of the carrier.Due to its large size and high cost,the traditional attitude and reference system severely limits the promotion of the AHRS in the civilian field.So it can only be applied to the military field.With the rapid development of Micro-Electro-Mechanical System(MEMS)and the consideration of cost factors,the application of micro-mechanical gyros and accelerometers has become more and more widespread.The application of MEMS-based attitude reference systems has received more and more attention.Therefore,the system has broad application prospects in both military and civilian fields.When the motion state of the carrier changes,the carrier attitude information provided by the AHRS in real-time may be deviated.Based on laboratory related projects,this paper proposes an extended Kalman filter fusion algorithm based on quaternion.The feasibility and effectiveness of the algorithm are verified by experiments.The algorithm lays the foundation for the wide application of MEMS attitude reference system.When MEMS inertial navigation is combined with the Global Navigation Satellite System(GNSS),it is possible to achieve a low-cost,wide-ranging,and small-sized design.This paper takes the low-cost MEMS attitude reference system and MEMS/GNSS integrated navigation system as the research object,and selects the appropriate algorithm in the dynamic environment to carry out a series of research work:(1)The standard Kalman filter,extended Kalman filter,unscented Kalman filter and adaptive Kalman filter are studied respectively.The application of the filter is analyzed and introduced.The attitude matrix updating algorithm is introduced,and the advantages and disadvantages of each algorithm are analyzed in this paper.(2)The measured data was obtained by running the car test with the MEMS inertial STIM300.According to the motion characteristics of the carrier and the system working requirements,the extended Kalman filter attitude fusion algorithm based on quaternion is selected by theoretical analysis of multiple attitude updating algorithms.Calculate the attitude of the measured data,and the calculation results show that the algorithm can meet the expected accuracy requirements.(3)The MEMS inertial working process needs to be assisted by GNSS information.In reality,the inertial navigation system is a nonlinear model.In addition,the accuracy of the carrier in the dynamic environment will be greatly affected.In this paper,UKF(Unscented Kalman Filter)filtering method is used for data solving,and the results of attitude calculation are compared with the results of MEMS/GNSS tight combination processing using Novatel's high-precision integrated navigation post-processing software Inertial Explorer 8.60.The experimental results show that the corresponding pitch angle and roll angle error are within 0.02°,and the position error is between-0.2m and 0.2m.