A Distributed Static Error Identification Method Based on Measurement Reconstruction for Dual-Axis Hybrid Inertial Navigation System

As fiber optic dual-axis hybrid inertial navigation systems (HINS) have been refined and popularized, changes in the operating mechanisms have rendered the traditional error identification system for strapdown inertial navigation systems (SINS) no longer applicable. Massive amounts of static data and tedious analysis tasks consume immeasurable costs, which are not conducive to the sustainable development of the HINS field. Moreover, current error identification studies are overly dependent on the external conditions and lack direct processing capabilities. To further improve performance and productivity, this article proposes a distributed static error identification method based on measurement reconstruction. Regarding the dual-axis HINS mechanism, the static error models and the attitude measurements are first established. Next, the trend and oscillation measurements are reconstructed through the extremum extension-empirical wavelet transform (E-EWT) algorithm, and the error parameters are optimally estimated by distributed filters. Finally, the simulation and the static long-duration experiment verify the feasibility and superiority of the method.