Research On Error Compensation Technology Of Redundant MEMS-IMU Based On KF

The strapdown inertial navigation system with redundant MEMS-IMU as the core component can take into account the advantages of high reliability and strong autonomy.It is widely used in aircraft,ship,robot,medicine and other fields.Since the main error source of INS comes from MEMS device error,redundant MEMS-IMU error compensation technology can be used to improve the navigation accuracy of sins.In practical engineering applications,due to the diversity of redundant configuration schemes,the existing calibration methods of redundant inertial measurement units can not be widely used.Therefore,the research on random error compensation and calibration technology of redundant MEMS-IMU is of great significance.In order to improve the accuracy and reliability of the redundant MEMS-IMU,the error characteristics of redundant MEMS-IMU,the random error compensation technology of MEMS,and the calibration technology of redundant MEMS-IMU are studied in this dissertation.The main work contents are as follows:Firstly,the error analysis of redundant MEMS-IMU is carried out.The random error characteristics of MEMS devices are analyzed;the installation error,scale factor error and constant error of redundant MEMS-IMU are analyzed,and the error model is determined;the problems of traditional calibration methods are analyzed to lay the foundation for the random error compensation and calibration of redundant MEMS-IMU.Secondly,the traditional MEMS Gyroscope Random error model is only based on the output data of the gyroscope,but with the change of the MEMS gyroscope environment,the parameters of the established random error model change.To solve this problem,an improved method is proposed to update the model parameters in real time.In order to solve the problem of poor filtering effect caused by the inaccuracy of the system noise matrix in the filtering process,a R~2-AKF filtering algorithm is proposed by introducing the concept of determining coefficient of goodness of fit.Dynamic and static experiments are designed to verify the algorithm.Thirdly,the laboratory calibration scheme of Redundant Strapdown Inertial Navigation gyroscope is designed.Aiming at the problems of low precision and complex calculation of traditional redundant MEMS-IMU error model,the small angle rotation vector method is used to improve the error model.Aiming at the problem that the rank of the observation matrix is less than the state quantity and the system is not completely observable,a zero space amplification algorithm is proposed to improve the observability of the system.Aiming at the problem that the calibration scheme based on Kalman filter is only suitable for linear system,a calibration scheme of redundant MEMS-IMU based on adaptive extended Kalman filter is proposed.Finally,taking the four redundant MEMS-IMU as the experimental object,the random error compensation and calibration experiments of the four redundant MEMS-IMU are carried out with the help of the three-axis inertial navigation system test table to verify the effectiveness of the calibration algorithm and the random error compensation algorithm.The experimental results show that the measurement accuracy of the gyroscope is greatly improved after the random error and deterministic error compensation are compensated.