An Improved Velocity Interval Estimation Method Based on Zonotopic Kalman Filter for Autonomous Underwater Vehicles
Abstract
Velocity plays a crucial role for the reliable operation of autonomous underwater vehicles. This paper investigates velocity interval estimation for autonomous underwater vehicles 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 method. Finally, pool experiments are conducted to validate the effectiveness of the proposed method.
Fields of Study & Subjects
Underwater Vehicles and Communication Systems
Target Tracking and Data Fusion in Sensor Networks
Inertial Sensor and Navigation
Publication details
- Journal / source
- IEEE Transactions on Instrumentation and Measurement
- Volume
- 75
- Pages
- 1–8
- Publication date
- 1 January 2026
- Language
- EN