Underwater Nonlinear Information Fusion Algorithm Based on Hydrodynamic Model
Luyu Luan, Hai Zhu · 2010
In order to improve the underwater vehicle positioning precision, a new underwater nonlinear information fusion algorithm based on hydrodynamic model and unscented Kalman filter was proposed. Hydrodynamic dead reckoning model represented sailing nonlinearity preferably, and the algorithm using unscented Kalman filter avoided linearization error. To confirm the position estimate capability of the nonlinear fusion algorithm, a sea trial was made. The results of sea trial demonstrate that the filtering accuracy and stability of the new nonlinear information fusion algorithm are better than Kalman filtering algorithm based on linear model. This nonlinear fusion algorithm can estimate position effectively even when underwater vehicle is maneuvering, and improve the estimated position precision of whole underwater sailing.