Single-beacon AUV navigation algorithm under period offset conditions

• Published in: Applied acoustics Vol. 231; p. 110522
• Main Authors: Zhang, Qingyu, Fu, Jin, Qi, Bin, Zou, Nan, Gao, Yongshuai
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2025
• Subjects: Arrival time; AUV; Signal cycle offset; TDOA; Arrival time; Signal cycle offset; AUV; TDOA
• ISSN: 0003-682X
• DOI: 10.1016/j.apacoust.2024.110522

•Navigation can still be completed robustly under the condition of signal period deviation.•The application conditions are looser than TDOA conditions, but consistent navigation accuracy can be achieved.•The impact of different measurement errors on the algorithm is analyzed through total differential equations•The effectiveness of the algorithm is verified through real lake experimental data. Underwater positioning and navigation technology is one of the key technologies for autonomous underwater vehicles to complete tasks efficiently. The navigation and positioning technology of single-beacon autonomous underwater vehicles has been highly valued because of its advantages such as simple and convenient placement. The existing implementation schemes are mainly based on arrival time information or arrival time difference information, and the prior knowledge they need includes synchronization time and signal cycle. However, due to the influence of the marine environment, such as low temperature and high pressure, the period of beacon transmission signal may be offset, resulting in navigation error increase or even failure. To solve this problem, this paper proposed a navigation method with looser application conditions, which is improved based on the TDOA algorithm, and it requires neither synchronization time nor signal cycle. Secondly, the influence of different motion trends on navigation accuracy and the influence of different measurement errors on the algorithm are analyzed by a full differential equation. Finally, the performance of the proposed algorithm is verified by simulation experiments and actual data. The results show that when the signal cycle is accurate, the accuracy of the proposed method is almost the same as that of the navigation algorithm based on TDOA; when the signal cycle offset leads to an increase in TDOA error or even failure, the method still has good adaptability and stability.