Optimization of SINS / GNSS Integrated Navigation Model Based on Prior Information

Inertial navigation systems (INS) are extensively utilized across various domains due to their independence from external information during operation, commendable autonomy and stealth, and capability to deliver comprehensive data output. The loose combination navigation of SINS/GNSS benefits from the complementing function of the Global Navigation Satellite System (GNSS), characterized by its straightforward principle and ease of implementation through the integration of GNSS data with the auxiliary correction provided by INS data. This work addresses the error issue in inertial navigation by proposing a filtering method utilizing a second-order Butterworth low-pass filter to extract a priori information from the inertial navigation data. Subsequently, it examines the impact of including a priori information on the efficacy of the SINS/GNSS loose-combination navigation. The findings indicate that incorporating a priori information can effectively rectify navigation trajectory deviations, enhance the convergence rate of misalignment angle errors, expedite the convergence of three-dimensional velocity errors in the northeastern sky, and diminish the amplitude of position error fluctuations. The precision of SINS/GNSS loose combination navigation is markedly enhanced.