Rapid alignment method based on local observability analysis for strapdown inertial navigation system

This paper presents a new method for rapid transfer alignment of strapdown inertial navigation system (SINS) by combining the local observability concept with robust adaptive filtering. The system state and observation models are simplified to analyze the observability of the SINS attitude error. Based on the simplified models, the observability matrix and its condition number are constructed to determine the observability degree of SINS during the process of rapid transfer alignment. On the basis of the local obsersability analysis, a robust adaptive filter is developed to estimate the attitude angle error for SINS rapid transfer alignment. Simulation experiments and comparison analysis have been conducted, demonstrating that the proposed method cannot only effectively measure the local observability of SINS, but it can also enhance the performance of SINS rapid transfer alignment and reduce the alignment time