A Unified Initial Alignment Method of SINS Based on FGO

Autor:	Zhou, Hanwen, Ye, Xiufen
Rok vydání:	2022
Předmět:	Computer Science - Robotics Electrical Engineering and Systems Science - Signal Processing
Druh dokumentu:	Working Paper
Popis:	The initial alignment provides an accurate attitude for SINS (strapdown inertial navigation system). By further estimating the IMU's bias and misalignment angle, the recursive Bayesian filter is accurate. However, the prior heading error has significant influence on the convergence speed and accuracy. In addition, the accuracy will be limited by its iteration at a single time-step. Coarse alignment method OBA (optimization-based alignment) uses MLE (maximum likelihood estimation) to find the optimal attitude quickly. However, few methods consider the IMU bias and misalignment angle, which will reduce the attitude accuracy. In this paper, a unified method based on FGO (Factor graph optimization) and IBF (inertial base frame) is proposed. The attitude is estimated by MLE, IMU bias and misalignment angle are estimated by MAP estimation. The state of all time steps is optimized together to further improve the accuracy. Physical experiments on the rotation MEMS SINS show that the heading accuracy of this method is improved in limited alignment time. Comment: 8 pages, This article has been accepted for publication in IEEE Transactions on Industrial Electronics
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2206.13348 Zobrazit plný text záznamu View this record from Arxiv