Optimal stochastic estimation of ship navigation parameters

The optimal estimation of a ship's navigation parameters as a nonlinear stochastic state estimation problem is considered. Performance evaluation of selected algorithms, the extended Kalman filter (EKF) and the decoupled filter, was accomplished for ship maneuvering and for different sensor configurations. For practical realization, a unique form of decoupled navigation estimator, originated by the author, is shown to be a good compromise between estimation accuracy and realization complexity.<>