Nonlinear innovation identification algorithm based on comprehensive application method for large ship model in rough sea

To avoid the parameter drift caused by dynamic cancellation in the process of large ship identification modeling in rough sea, and further improve the navigation stability of large ship. The authors combine two measures of parallel processing and estimation of too large and too small initial values to form a comprehensive application method. A nonlinear innovation extended kalman filter algorithm based on the comprehensive application method is proposed to avoid the hydrodynamic coefficients drift in rough sea. The experimental results indicate that after introducing the comprehensive application method and the nonlinear innovation algorithm, the proposed algorithm has the characteristics of strong resolving ability, high identification efficiency and small calculation burden of the large ship head wind and wave navigation. At the same time, the proposed algorithm avoids the phenomenon of parameter drift caused by dynamic cancellation. The experimental results are highly fitted with the actual ship data, which provides the basis for the stable navigation of large ship in rough sea.