Research On Key Technology Of AHRS Based On MEMS Inertial Sensors

Attitude and Heading Reference System(AHRS)based on Micro-Electro-Mechanical Systems(MEMS)inertial sensors has been extensively used in our daily life,industry and even military due to the outstanding advantages of low power consumption,low cost and small size.But on the other hand,the issues created by the accuracy of the sensor,the accuracy of the attitude calculation method,and the high sensibility of the external environment,restrict its accuracy of the output attitude and prohibit its widespread utilization.This thesis,aiming at expanding its application scope,promotes the accuracy of AHRS attitude information by studying the key technologies involved in the AHRS of MEMS.The source errors,which affect the precision of attitude information,include errors of MEMS inertial sensor,errors of magnetometer itself,errors of the random noise,errors caused by interference of external accelerations and the errors of MEMS inertial sensor output information.To eliminate those errors,this thesis presents the following research ideas and methods:First of all,calibrating the MEMS inertial sensor.This thesis comes up with a “weighting least square” method to calibrate the errors of the gyroscope and the deterministic errors which come from the accelerometer itself.It can effectively restrain the fitting error generated during the process of applying the least square on the large error of measurement,and improve the accuracy calibration of the deterministic errors;in this thesis the random error model,established by ALLAN variance method,is used to analyze the random errors.Since the output of the magnetometers contains its own errors,a circular model based on the ellipse theory is built to calibrate the magnetometers.Secondly,suppressing the variance of random noise.This thesis introduces a real-time variance of random noise updating based on Bayesian Laplacian Kalman Filtering(BLKF)method.It signifies the Bayesian posterior edge distribution by means of the Laplacian approximation algorithm,and corrects the variance of random noise in real time to increases the accuracy of variance.Meanwhile,it can also avoid inaccurate filtering results which might be led by the variance of random noise of Kalman Filtering(KF).BLKF and KF were applied respectively according to the experimental data acquired from the gyroscope turntable on the rotary table.By comparing the filtering results,it proves that BLKF reflects the true angular velocity in a better way than KF.Thirdly,eliminating the external acceleration.This work offers a method to eliminate the external acceleration of accelerometer data by using secondary Cubature Kalman Filtering(CKF).By studying if there exists significant difference in measurement noise under the condition with and without external acceleration,it constructs a difference model between the real measurement value and the estimated measurement value,which updates the measurement in terms of the secondary CKF,so as to eliminate the influences which arouse when accelerometer measures the gravitational acceleration.Fourthly,the MEMS inertial sensor output information fusion.This thesis suggests a method that solves that attitude information in accordance with output data of the CKF fusion gyro,the accelerometer and the magnetometer;it also suppresses the diffuse phenomenon which arises when the angular velocity of gyroscope solves the attitude information by integral accumulation.By employing the accelerometers and output information from magnetometer as the measurement,gyroscope output angular velocity as the state quantity to estimate the quaternion,the CKF model is constructed and the accurate pose information is obtained in the light of filtering model.Last step,experiment data calculation.After comparing experimental results to the AHRS information produced by SBG,it validates the feasibility and the accuracy of the calculation of attitude in this work.The results reveals that the method in this work may shed light on raising the accuracy of the output attitude information of AHRS,and it also complies with the output attitude information of attitude and heading reference system which is produced by SBG.In conclusion,there is a high engineering application value in the method proposed in this thesis.