Calibration of MEMS Accelerometer Using Kaiser Filter and the Ellipsoid Fitting Method

MEMS accelerometer, the key component of the Inertial Navigation System (INS), has been widely applied in various electronic consumption fields such as mobile phones and unmanned vehicles. However, it suffers from the scale factor errors, constant biases, and misalignment errors. These calibration errors which are not fully compensated may remain in the initial alignment of the INS, and result in attitude errors. In order to address this problem, this paper presents an efficient calibration method of MEMS accelerometer based on Kaiser filter and the ellipsoid fitting. At first, the raw data from the output of the accelerometer will be filtered by using the Kaiser filter. In the second stage, the mathematical error model of the accelerometer is constructed via ellipsoid fitting. Subsequently, the calibration scheme will be given. The experimental results show that the output of the calibrated tri-axis MEMS accelerometer is close to the standard value, and the absolute error of the pitch angle calculated by the accelerometer is reduced from 4.431 degrees (before compensation) to 0.735 degrees (after calibration). Compared with the traditional six-position calibration method, the accuracy of the MEMS accelerometer is significantly improved more than 36% by applying the proposed algorithm. Therefore, it is feasible and advantageous to apply the presented calibration algorithm for improving the measurement accuracy of the MEMS accelerometer.