Abstract
To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
Highlights
China faces an increasing demand for marine resources and ocean space along with economic and social development, bringing a variety of practical challenges to its maritime regulation and security
Ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were extracted
The analysis reveals that the prediction performance of the trained model was dramatically improved when the trajectory was reasonably partitioned and trajectory features were extracted from sub-trajectories
Summary
China faces an increasing demand for marine resources and ocean space along with economic and social development, bringing a variety of practical challenges to its maritime regulation and security. Computers are able to automatically learn the regular movement and behavioral patterns of ships [2]. In this way, the analysis can assist maritime supervisors and military commanders in rapidly locating any suspected and abnormal target based on the massive quantities of information on ship trajectory. The analysis can assist maritime supervisors and military commanders in rapidly locating any suspected and abnormal target based on the massive quantities of information on ship trajectory This analysis is combined with other detection means to comprehensively judge the actual identity of suspected and abnormal maritime targets and their purposes
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