Optimization-based Alignment for Strapdown Inertial Navigation System Comparison and Extension

TL;DR

This paper enhances optimization-based alignment methods for strapdown inertial navigation systems by enabling gyroscope bias estimation and evaluates their performance with various vector observation procedures using field data.

Contribution

It extends OBA to estimate gyroscope biases alongside attitude and provides a comprehensive evaluation of different vector observation methods.

Findings

Extended OBA to include gyroscope bias estimation.

Compared convergence speed and accuracy of methods.

Field tests show improved alignment performance.

Abstract

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.