It is difficult to achieve comprehensive parameter identification in multiple dimensions and degrees of freedom using traditional parameter identification methods. In order to obtain the real-time complex parameters and attitude information of ships, and ensure the stability and safety of ships during navigation, an improved wild horse optimizer (IWHO) is introduced into the ship parameter identification method. It is then combined with traditional ship identification methods to improve the accuracy of ship parameter identification.

On the basis of establishing a longitudinal motion model of the ship, a dynamic inertia weight design is introduced to further optimize the wild horse optimizer and complete the design of the longitudinal parameter identification method.

By comparing and analyzing the tracking performance of ship identification models using different algorithms, as well as the identification results of ship parameters under different wave encounter angles, it is found that IWHO has an identification error of about 1%, which is lower than those of other algorithms. Therefore, the identification model of this algorithm has a more accurate tracking effect on the ship's attitude during navigation.

The proposed identification method can provide accurate parameters in real time, improve operability and ensure the stability and safety of ship navigation.