Underwater terrain positioning method based on Markov random field for unmanned underwater vehicles

Frontiers in Marine Science

Marine Science

Xiaolong Chen¹  Ying Liu²  Pengyun Chen³  Lei Zhang⁴  Teng Ma⁴ 

[1] China Ship Development and Design Center, Wuhan, China;College of Oriental Languages, Harbin Normal University, Harbin, China;School of Aerospace Engineering, North University of China, Taiyuan, China;Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China;

关键词: unmanned underwater vehicles;    Markov random field (MRF);    multi-beam sounding data;    terrain-aided navigation;    semi-physical simulation;   

DOI  :  10.3389/fmars.2023.1201716

 received in 2023-04-07, accepted in 2023-05-08,  发布年份 2023

来源: Frontiers

【 摘 要 】

Underwater terrain-matching navigation technologies have become a popular topic for the high-precision positioning and navigation of autonomous underwater vehicles. This paper proposes an underwater terrain-matching positioning method based on a Markov random field model, which is based on real-time terrain data obtained using a multi-beam echo sounder. It focuses on the strong correlation between adjacent terrain data, which can improve terrain adaptability and matching accuracy. Playback simulation tests were conducted based on actual sea trial data, and the results showed that the proposed method has good positioning performance, which can correct the cumulative errors of inertial navigation systems. The results demonstrated the usability of the proposed method for positioning correction in underwater engineering applications.

【 授权许可】

Unknown   
Copyright © 2023 Chen, Liu, Chen, Ma and Zhang