@inproceedings{bc7c4e2e40b8407da4dc7657d53fa858,
title = "SINS In-Motion Initial Alignment Based on Backtracking Multi-vector Attitude Determination",
abstract = "Backtracking alignment is essentially a data multiplexing technology, which uses reverse navigation and data fusion to obtain better results than traditional methods. Since the multi-vector attitude determination (MAD) method is widely used in the in-motion alignment, it can be considered to combine this method with backtracking to further improve alignment accuracy. In this paper, an in-motion alignment method based on backtracking multi-vector attitude determination (BMAD) is proposed. Part of results in the forward process are stored and reused in the reverse alignment. Then an information fusion method based on iterative matrix eigenvalues is further proposed to improve yaw alignment accuracy. Simulation experiment is designed and compared with backtracking alignment based on Kalman filter to verify the effectiveness of the method.",
keywords = "Backtracking, Information fusion, Multi-vector attitude Determination, Reverse navigation",
author = "Xuan Xiao and Yongyan Zhang",
note = "Publisher Copyright: {\textcopyright} 2022 Technical Committee on Control Theory, Chinese Association of Automation.; 41st Chinese Control Conference, CCC 2022 ; Conference date: 25-07-2022 Through 27-07-2022",
year = "2022",
doi = "10.23919/CCC55666.2022.9901640",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "3323--3328",
editor = "Zhijun Li and Jian Sun",
booktitle = "Proceedings of the 41st Chinese Control Conference, CCC 2022",
address = "United States",
}