Underwater terrain positioning method based on Markov random field for unmanned underwater vehicles - Chen, Pengyun; Liu, Ying; Chen, Xiaolong; Ma, Teng; Zhang, Lei (Frontiers in Marine Science, 2023)
To achieve high-precision underwater positioning and navigation for autonomous underwater vehicles, underwater terrain matching navigation technologies have become a research hotspot. An underwater terrain-matching positioning method based on Markov random field model is proposed in this research, which is based on real-time terrain data obtained by a multi-beam echo sounder. It focuses on the strong correlation between adjacent terrain data, which can help improve terrain adaptability and matching accuracy. Playback simulation tests are carried out based on real sea trial data; the results show that the proposed method has good positioning performance, which can correct the cumulative errors of inertial navigation system. This establishes the usability of the method in positioning correction in special underwater engineering fields.