An Improved Cooperative Navigation Method for Slave AUV Under the Influence of Ocean Currents

The implementation of a master-slave Autonomous Underwater Vehicle (AUV) system significantly reduces expenses while enhancing task efficiency. Precise underwater navigation and positioning is crucial for the safe navigation and successful execution of predefined tasks by AUVs. This paper focuses on master-slave AUV cooperative navigation, aiming to solve the challenges of declining navigation accuracy over time during the slave AUV underwater missions as well as the limited calibration range of fixed beacons. Firstly, to address the issue of vehicle drift caused by ocean currents in complex marine environments, a collaborative navigation model was developed by adding ocean current velocity as a state variable, and positioning algorithms were formulated using five common filtering methods; Secondly, considering that noise is difficult to estimate accurately, adaptive particle swarm optimization is added to the algorithm to improve the overall positioning performance; Finally, a collaborative navigation experiment was carried out at sea to compare and analyze the effectiveness of the algorithm. The experimental results demonstrate that the proposed method can effectively improve the positioning accuracy of the slave AUV.