Collaborative Calibration Algorithm in Redundant Dual-axis RINS Configuration

Dual-axis rotational inertial navigation system (DRINS) can achieve self-calibration of error parameters to improve the navigation performance. However, the traditional self-calibration methods rely on the external reference information. This paper focuses on the dual DRINSs configuration and proposes a collaborative calibration algorithm. Considering the error parameters of redundant DRINS, the 60-D Kalman filter is established, in which the geometric constraint between systems are deployed to establish the observation equation without external reference information. A novel collaborative calibration scheme is designed based on the asynchronous rotation to make all the error states observable. Monte Carlo simulations and real system experiments are conducted to verify the effectiveness of the proposed algorithm. The result shows the algorithm works well.