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.

The Kalman filter method plays a crucial role in enhancing the navigation accuracy of the dual-axis rotational inertial navigation system (RINS) through periodic estimation and compensation of device errors. Due to the particularity of polar geography, the traditional RINS mechanism in the local-level geographic frame loses efficacy in the polar region. This paper proposes a self-calibration Kalman filter algorithm based on the transverse ellipsoidal earth model to solve the self-calibration problem of RINS in polar region. This method firstly transforms the state of the local-level geographic frame to the transverse frame, and then constructs the prediction model and observation model of the Kalman filter based on the carrier state and error parameters in the transverse frame. In the self-calibration stage, a suitable rotation strategy is employed to stimulate the errors of RINS, and the proposed algorithm is utilized to estimate and compensate for the resulting errors. In addition, the traditional spherical earth model is improved to ellipsoidal earth model in this algorithm to avoid additional errors in the polar region. Monte Carlo experiments are carried out with simulation data at high latitudes, and then experiments at middle latitudes are carried out with ring laser gyro-based dual-axis RINS. The results demonstrate that the proposed method enables precise calibration of all error parameters, which aligns consistently with results obtained within the local-level geographic frame.