Calibration and Attitude Determination with Redundant Inertial Measurement Units

Abstract

A calibration filter is developed for redundant inertial measurement units, which are inertial measurement units that have more than three sense axes. It is shown that for a Kalman filter based on an attitude measurement model and an attitude kinematics model in the “model replacement mode,” a linear combination of the calibration parameters is not observable and therefore cannot be estimated. This observability problem is not related to dynamic observability, which requires calibration maneuvers. A null-space measurement equation, together with the attitude measurement and kinematics models, provides complete observability so that all calibration parameters can be estimated. Estimator performance without and with the null-space measurement update is demonstrated via simulation results.