Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation with narrow-field-of-view (NFOV) star tracker is widely employed in the aviation and aerospace fields contributed by its high accuracy and autonomy. However, due to the computational cost and data transmission of CNS, the output data of CNS and SINS cannot be completely synchronized, which seriously affects the performance of integrated navigation, particularly in highly dynamic environments. To solve the problem above, this article constructs a model and proposes an online calibration method for the asynchronous time between the outputs from SINS and CNS with NFOV star tracker. First, the error characteristic of SINS/CNS asynchronous time is analyzed, and the imaging detection is revealed to be significantly affected by the SINS/CNS asynchronous time in dynamic environments. Additionally, on the basis of the error characteristic analysis, a corresponding error model is established. Finally, an online calibration scheme of SINS/CNS asynchronous time is designed based on the backtracking navigation algorithm. Simulations and field experiments show that the online calibration method works well in calibrating the SINS/CNS asynchronous time and compensating for the tri-axis attitude misalignment angles of the SINS, affirming the efficacy and feasibility of the established model and proposed calibration method in this article.
[6]
Kai Wang, 2021, 2021 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), P1098, DOI 10.1109/AEECA52519.2021.9574189
[6]
Kai Wang, 2021, 2021 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), P1098, DOI 10.1109/AEECA52519.2021.9574189