An Improved Velocity Interval Estimation Method Based on Zonotopic Kalman Filter for Autonomous Underwater Vehicles

Velocity plays a crucial role for the reliable operation of autonomous underwater vehicles (AUVs). This article investigates velocity interval estimation for AUVs with parametric uncertainties. The proposed method employs zonotopic reachability analysis to obtain an envelope that contains all possible state values. By incorporating a novel T-N-L structure, the width of the estimated interval is reduced by 25.5% relative to the conventional zonotopic Kalman filter (ZKF) method. Finally, pool experiments are conducted to validate the effectiveness of the proposed method.