Abstract:Accurately identifying the angle of attack and speed of underwater vehicles relative to ocean currents holds significant importance for various operations. These include motion control of underwater vehicles in complex ocean current environments, identification of launch windows for underwater weapons, and the perception and warning of internal ocean waves. This paper uses the Suboff submarine model as the research subject to investigate methods for identifying the relative current angle of attack and speed of underwater vehicles based on the principle of biomimetic flow field perception. Initially, Computational Fluid Dynamics (CFD) and potential flow simulation models were established to study the flow fields surrounding underwater vehicles. It was discovered that for predicting unsteady pressure at the head of underwater vehicles, the results from CFD and potential flow simulations are very similar. Consequently, it is feasible to use the potential flow model to quickly and accurately predict the head pressure of underwater vehicles at high angles of attack. Following this, a flow field parameter identification model for underwater vehicles was developed by integrating potential flow theory with Kalman filtering. Both simulation and experimental results demonstrated that the flow field parameter identification model can achieve an identification error within 3 degrees for the angle of attack across a range of ±80 degrees, and the relative error for speed recognition is within 5%.?? (Note: The original text provided was already mostly in English; this response refines and completes the translation ensuring clarity and coherence.)
