TY - GEN
T1 - Research on AUV Cooperative Positioning Technology Based on Improved-EKF with Error Estimation
AU - Yuan, Hui
AU - Wei, Jianxiong
AU - Shao, Jianbo
AU - Fan, Shiwei
AU - Yu, Fei
AU - Huang, Wenjun
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Aiming at the data fusion problem in the Leader-fellow cooperative positioning system of multiple autonomous underwater vehicles (AUV), the mathematical model of the Leader-fellow cooperative positioning system is established, and then the speed error and heading error are analyzed to position the fellow AUV At the same time, an improved- EKF filtering algorithm with the ability to estimate the measurement error of navigation equipment is designed. The distance information between the leader and fellow AUVs obtained by acoustic ranging is used as the measurement information to estimate the position, speed error and heading error of the fellow AUV. In order to verify the effectiveness of the algorithm, the cooperative positioning algorithm with error estimation capability is verified by simulation experiments and offline data from ship navigation experiments on the lake. The results show that the proposed improved-EKF algorithm can effectively reduce the positioning error of the fellow AUV. It is especially obvious when the AUV is autonomously positioned, which greatly improves the navigation and positioning capabilities of the fellow AUV.
AB - Aiming at the data fusion problem in the Leader-fellow cooperative positioning system of multiple autonomous underwater vehicles (AUV), the mathematical model of the Leader-fellow cooperative positioning system is established, and then the speed error and heading error are analyzed to position the fellow AUV At the same time, an improved- EKF filtering algorithm with the ability to estimate the measurement error of navigation equipment is designed. The distance information between the leader and fellow AUVs obtained by acoustic ranging is used as the measurement information to estimate the position, speed error and heading error of the fellow AUV. In order to verify the effectiveness of the algorithm, the cooperative positioning algorithm with error estimation capability is verified by simulation experiments and offline data from ship navigation experiments on the lake. The results show that the proposed improved-EKF algorithm can effectively reduce the positioning error of the fellow AUV. It is especially obvious when the AUV is autonomously positioned, which greatly improves the navigation and positioning capabilities of the fellow AUV.
KW - AUV
KW - Cooperative positioning
KW - Error estimation
KW - Improved-EKF
UR - https://www.scopus.com/pages/publications/85125176171
U2 - 10.1109/CCDC52312.2021.9601673
DO - 10.1109/CCDC52312.2021.9601673
M3 - 会议稿件
AN - SCOPUS:85125176171
T3 - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
SP - 391
EP - 396
BT - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Chinese Control and Decision Conference, CCDC 2021
Y2 - 22 May 2021 through 24 May 2021
ER -