Abstract: Ship motion modeling is crucial for developing intelligent control technology. Traditional modeling methods, however, have drawbacks such as a large number of parameters and insufficient precision. To address these issues, this paper focuses on the latest intelligent research and training ship "Xin-Hong-Zhuan" of Dalian Maritime University. A ship motion characteristic model is constructed using the characteristic modeling method. First, the study begins with Kalman filtering to preprocess real-ship test data. Next, the nonlinear innovation recursive least squares method with a forgetting factor is used to identify the model's parameters. Finally, turning circle tests and zigzag maneuver tests are conducted to verify the model's effectiveness and accuracy. The results show that the model has an agreement of 89.7%, fewer parameters, and higher precision than the traditional Nomoto model. This research offers a theoretical reference for applying characteristic models in navigation and is significant for improving the precision of ship motion control.