A Rapid and Self-Contained Calibration Method for MIMUs Based on Residual Velocity Measurement

In micro inertial measurement units (MIMUs), the zero bias, scale factor error, and non-orthogonal error in both gyroscopes and accelerometers will lead to cumulative errors in inertial navigation computation. This paper proposes a rapid, self-contained calibration method for estimating the MIMU output model based on residual velocity measurement, which significantly reduces calibration time and enhances estimation accuracy without requiring high-precision turntables or external references. First, a comprehensive output model of the MIMU is established. Subsequently, a self-contained calibration model based on a Kalman filter is developed, utilizing residual velocity and the difference between gravity-integrated velocity and inertial navigation velocity. Then, an oriented rotation scheme is designed by a self-developed spherical rotation platform, and the observability for parameters in the MIMU output model is analyzed. Finally, the simulation results indicate that the parameters in the MIMU output model can be successfully estimated within 390 s, achieving an estimation accuracy exceeding 85%. The static and dynamic scenario navigation experiment results demonstrate the effectiveness of the proposed self-contained calibration. Collectively, the proposed method provides a rapid, convenient, and self-contained calibration solution for MIMUs.