Optimization-based Alignment for Strapdown Inertial Navigation System Comparison and Extension
This work addresses the alignment accuracy and efficiency for inertial navigation systems, which is incremental as it builds on existing OBA methods.
The paper tackles the problem of aligning strapdown inertial navigation systems (SINS) by extending optimization-based alignment (OBA) methods to estimate gyroscope biases and evaluating different vector observation procedures using field test data, resulting in improved convergence speed and steady-state estimates for various SINS grades.
In this paper, the optimization-based alignment (OBA) methods are investigated with main focus on the vector observations construction procedures for the strapdown inertial navigation system (SINS). The contributions of this study are twofold. First the OBA method is extended to be able to estimate the gyroscopes biases coupled with the attitude based on the construction process of the existing OBA methods. This extension transforms the initial alignment into an attitude estimation problem which can be solved using the nonlinear filtering algorithms. The second contribution is the comprehensive evaluation of the OBA methods and their extensions with different vector observations construction procedures in terms of convergent speed and steady-state estimate using field test data collected from different grades of SINS. This study is expected to facilitate the selection of appropriate OBA methods for different grade SINS.