Model-Aided Navigation with Sea Current Estimation for an Autonomous Underwater Vehicle

This paper presents a strategy to improve the navigation solution of the HRC-AUV by deploying a model-aided inertial navigation system (MA-INS). Based on a simpler three-DOF linear dynamic model (DM) of the vehicle, and implemented through a Kalman filter (KF), the performance of the proposed MA-INS is compared to state-of-the-art solutions based on non-linear models. The model allows the online estimation of the sea current parameters before and during the navigation mission. Qualitative and quantitative evaluations as well as a statistical significance test are performed using both simulated and real data, demonstrating the usefulness of the proposed model-aided navigation.

CRIS-UCLV