Application of the ensemble Kalman filter to unsteady inflow reconstruction for an axisymmetric body

Environmental perception is a crucial issue for underwater vehicles. This study investigates the use of the ensemble Kalman filter to reconstruct unsteady currents ahead of these vehicles by sampling the surrounding flow fields at scattered locations, which leads to an inverse problem. To mitigate the high computational cost associated with Monte Carlo methods, an axisymmetric simulation is employed for data assimilation. Therefore, it is important to discuss the influence of factors such as observation noise, sample size, and covariance inflation parameters on the final performance, especially when compared to the full three-dimensional model. The results suggest that while most of the error stems from model discrepancies, careful parameter selection can effectively control the error within acceptable limits.