Ship trajectory prediction method based on bayesian optimization of directional inertia correction
By employing a Bayesian-optimized orientation inertia correction method, combined with inertia decay, orientation calibration, and affine coordinate transformation, the problem of insufficient accuracy of traditional models in complex marine environments is solved, achieving efficient and interpretable ship trajectory prediction, which is suitable for maritime traffic management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JIMEI UNIV
- Filing Date
- 2026-04-21
- Publication Date
- 2026-07-17
AI Technical Summary
Existing ship trajectory prediction technologies struggle to achieve an ideal engineering balance between accuracy, efficiency, and interpretability. Traditional models cannot adapt to the dynamic nature of complex marine environments, while deep learning models suffer from high computational costs and poor interpretability, failing to meet the needs of maritime traffic safety early warning and management.
The Bayesian optimization-based orientation inertia correction method for ship trajectory prediction achieves high-precision prediction with a lightweight model by automatically determining parameters through inertia decay, orientation calibration, affine coordinate system transformation, and trajectory smoothing mechanisms, combined with the Bayesian optimization algorithm.
It achieves high-precision, low-computational-cost ship trajectory prediction in complex marine environments, making it suitable for deployment on shipborne edge devices with limited computing resources, and providing reliable maritime traffic safety support.
Smart Images

Figure CN122410992A_ABST