Research On Key Technology Of Mems Inertial Attitude Reference System

Attitude Heading Reference System(AHRS)which based on micro-electro-mechanical system(MEMS)has the advantages of small size,low cost,and high reliability,which can meet the needs of miniaturized market.However,the output of AHRS is constrained by the performance of the sensors and the external environment.In order to improve the accuracy of AHRS attitude,this paper includes related research on the key technologies of AHRS based on MEMS technology.The main research contents are as follows:1.The research status of MEMS sensors and AHRS are introduced,and the commonly used attitude caculate algorithms are explained and analyzed in detail.2.Since the sensors is one of the important factors that limit the solution results,mathematical models of MEMS gyroscope,MEMS accelerometer,and triaxial magnetometer are established in this paper,and the error characteristics of each sensor are analyzed.In order to compensate the sensor error,the rotation modulation technology is introduced.Sensor error can be estimated and the divergence of navigation error can be suppressed according to the error propagation law without external assistance.The navigation accuracy of the system improved by rotation modulation technology,and according to the traditional single-axis rotation method a continuous biaxial rotation scheme is proposed.3.A low-cost sensor calibration method is proposed.This method can efficiently and cost-effectively calibrate the sensors built in AHRS,and provide accurate measurement data for subsequent attitude calculations.A fast iterative algorithm is proposed for calibrating the accelerometer.This method improves the running speed while ensuring the calibration accuracy.According to the calibrated accelerometer output data,the three-axis gyroscopes and the three-axis magnetometers are calibrated in turn,and calibration experiments are performed to verify them.4.When works in a dynamic environment,the external acceleration will interfere with the measurement of the accelerometer and then affect the accuracy of the AHRS.Two commonly used attitude calculation methods are introduced.One of them is to consider that the motion acceleration is a random walk process driven by white noise.Based on this,the external acceleration is estimated,thereby eliminating the influence of the external acceleration.Another commonly used method is a conventional adaptive algorithm.This method is to set a threshold to determine whether there is an external acceleration and increase the corresponding measurement noise covariance,However,the method is too simple and direct,and it is easy to be misjudged by the accelerometer’s own noise.It cannot compensate for each axis of the accelerometer separately,and it is easy to lose useful information.In this paper,an adaptive filtering algorithm based on EKF is designed.The adaptive algorithm can adjust the filter in real time according to the external acceleration,improve the accuracy of the solution in dynamic environment.The attitude information provided by the French SBG’s Ellipse2-A system is selected as a reference,and several sets of experiments are designed to verify the effectiveness of the algorithm.The research results show that the research content of this paper has a certain effect on improving the accuracy of AHRS attitude solution.The adaptive filtering algorithm proposed in this paper can effectively suppress the impact of external acceleration on the attitude calculation.