Research On The Technology Of Heading And Attitude Measurement System Based On MEMS-IMU

The emergence of MEMS technology leads to a great change of inertial navigation technology. It makes the inertial navigation system more compact, low-cost and low-power.In particular, the emergence of MEMS-IMU makes the inertial navigation system towards the"micro-system" which is a set of sensors and processors. Given the huge potential applications of MEMS technology in the aerospace and military fields, the study of MEMS-IMU becomes a hot research field of inertial navigation.The research of this thesis is based on a strapdown heading and attitude measurement system which uses a MEMS-IMU module as the core measurement unit. The main research contents of this thesis is error modeling and calibration technology for MEMS-IMU, initial alignment of the heading and attitude measurement system, and attitude updating algorithm based on the adaptive Kalman filtering.First, this thesis briefly introduced the research background and significance, elaborated the development process and huge application advantage of MEMS inertial devices. This thesis briefly introduced the constitution of the measurement unit in the system, determined to use an accelerometer and a magnetometer which are respectively sensitive to the gravity vector and magnetic vector to assist gyroscope attitude measurement. This constitution has obvious advantages, it makes up the defect of errors accumulate over time when the system only uses gyro attitude determination.Then, this thesis gave the definition of the reference frame, heading and attitude,analyzed the establish process and immediate correction algorithmof the strapdown matrix.This thesis also introduced the basic architecture of the system's hardware platform,especially about the features of MEMS-IMU.Next, for the characteristics of MEMS devices, this thesis analyzed the error sources.According to the system requirements, this thesis selected bias, scale factor, and non-orthogonal installation error factor as the main error sources, and established the appropriate error models. For the calibration of MEMS devices, this thesis also gave the specific calibration methods, completed the calibration experiment for gyroscope and accelerometer, gave the calibration results, and verified the accuracy of the results. It shows that the calibration method for MEMS-IMU is feasible.Later, this thesis introduced the basic theory of Kalman filtering and made a brief analysis, elaborated the system's initial alignment process, and gave the solving method of the initial strapdown matrix. Based on the basic principle of the Kalman filter, this thesis uses the quaternion error and gyro bias error as state variables, and uses the accelerometer and magnetometer error as observed variables. Then, this thesis completed the design of adaptive Kalman filter for the heading and attitude measurement system, achieved the optimal estimation attitude angle, and gave the regulation rules of the adaptive parameters.Finally, this thesis completed system performance tests under disturbed condition,specifically analyzed the impact of the gyroscope bias on system performance. The system tests identified the adaptive filter parameters, verified that the system can work stably at low dynamic environment, and also showed that the the system algorithm is feasible.