TY - GEN
T1 - A New Multiple State Estimation Cooperative Positioning Method Based on MEMS/Underwater Acoustic Ranging for Multiple UUVs
AU - Wang, Qingxin
AU - Gao, Wei
AU - Fan, Shiwei
AU - Zhang, Ya
AU - Li, Guangmin
AU - Wang, Yanyan
AU - Guo, Kun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In the traditional cooperative positioning scheme, navigation information is provided from the compass and doppler velocity log. These sensors are large and expensive. To meet the needs of low cost and miniaturization, a new cooperative positioning scheme based on Micro-Electro-Mechanical System (MEMS)/underwater acoustic ranging is designed in this paper, and a multiple state estimation cooperative positioning method based on ranging information is proposed. Specifically, MEMS is the main source of navigation information for follower underwater unmanned vehicle (UUV), and underwater acoustic ranging information is the constraint. Finally, the attitude, velocity, position of follower UUV in three directions as well as the three-axis gyro drift and the three-axis accelerometer bias of MEMS are estimated by utilizing the ranging information. The effectiveness of our scheme and methodology is thoroughly validated through simulations and experiments. Importantly, our proposed method demonstrates a significant improvement in positioning accuracy, outperforming the traditional approach by an impressive 68.75%. This remarkable enhancement highlights the efficacy and reliability of our innovative solution.
AB - In the traditional cooperative positioning scheme, navigation information is provided from the compass and doppler velocity log. These sensors are large and expensive. To meet the needs of low cost and miniaturization, a new cooperative positioning scheme based on Micro-Electro-Mechanical System (MEMS)/underwater acoustic ranging is designed in this paper, and a multiple state estimation cooperative positioning method based on ranging information is proposed. Specifically, MEMS is the main source of navigation information for follower underwater unmanned vehicle (UUV), and underwater acoustic ranging information is the constraint. Finally, the attitude, velocity, position of follower UUV in three directions as well as the three-axis gyro drift and the three-axis accelerometer bias of MEMS are estimated by utilizing the ranging information. The effectiveness of our scheme and methodology is thoroughly validated through simulations and experiments. Importantly, our proposed method demonstrates a significant improvement in positioning accuracy, outperforming the traditional approach by an impressive 68.75%. This remarkable enhancement highlights the efficacy and reliability of our innovative solution.
KW - MEMS
KW - cooperative positioning
KW - multiple state estimation
KW - underwater unmanned vehicle (UUV)
UR - https://www.scopus.com/pages/publications/85170823562
U2 - 10.1109/ICMA57826.2023.10216016
DO - 10.1109/ICMA57826.2023.10216016
M3 - 会议稿件
AN - SCOPUS:85170823562
T3 - 2023 IEEE International Conference on Mechatronics and Automation, ICMA 2023
SP - 1352
EP - 1357
BT - 2023 IEEE International Conference on Mechatronics and Automation, ICMA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Mechatronics and Automation, ICMA 2023
Y2 - 6 August 2023 through 9 August 2023
ER -