Navigation vector based ship maneuvering prediction

Abstract

A novel mathematical framework for predicting ship maneuvers within a short time interval is presented in this study. The first part of this study consists of estimating the required vessel states and parameters by considering a kinematic vessel maneuvering model. That is supported by an extended Kalman filter (EKF), where vessel position, heading, yaw rate and acceleration measurements are used. Then, the estimated vessel states and parameters are used to derive the respective navigation vectors that consist of the pivot point information. The second part of this study consists of predicting the future vessel position and orientation (i.e. heading) within a short time interval by a vector product based algorithm, where the respective navigation vectors are used. The main advantage in this method is that the proposed framework can accommodate external environmental conditions and that feature improves the predictability of vessel maneuvers. Finally, the proposed mathematical framework is simulated and successful computational results in predicting ship maneuvers are presented in this study. Therefore, that can be implemented in modern integrated bridge systems to improve the navigation safety in maritime transportation.