Ship wandering detection method based on AIS data

Abstract

The invention discloses a ship wandering detection method based on AIS data, and the method can achieve the detection of the wandering behaviors of a ship according to the obtained AIS track data of the ship and the massive track data, classifies the wandering behaviors of the ship, and summarizes the relation between the tracks of four types of typical abnormal motion behaviors of the ship and adefined variable. According to the relationship between the ship motion trail characteristics and the statistical parameters, analysis is performed and the abnormal wandering behavior of the ship is detected according to the trail distribution condition in the grid. After the ship AIS track is filtered and smoothened, a global space-time grid index is established, gridding processing is conductedon the ship track, ship abnormal motion is detected according to ship abnormal behavior track characteristics, and abnormal classification alarming is conducted on ship motion behavior track abnormity. The ship wandering behavior detection can provide decision support for marine safety supervision, enhances marine traffic safety, ensures safe sailing of the ship, and has important significance forpromoting marine transportation to be safe, efficient and smooth.

Description

technical field [0001] The invention relates to the field of big data analysis, in particular to a ship loitering detection method based on AIS data. Background technique [0002] In recent years, with the continuous increase in the number and density of ships at sea, the ship trajectory data has increased on a large scale. At the same time, the difficulty of maritime traffic safety management has also increased. It is necessary to conduct deeper analysis and processing of ship track data in order to enhance the safety of maritime traffic. . At present, more and more scholars use the data information provided by the equipment of the ship automatic identification system to conduct research on maritime traffic. [0003] According to the behavior of the ship's trajectory, when non-fishing ships have approximate loitering behavior, these abnormal behaviors are often related to drunk driving, hijacking, illegal fishing, piracy, and illegal measurement. Then its trajectory lengt...

AI Technical Summary

Problems solved by technology

The traditional detection of ship loitering behavior is not highly targeted, and cannot classify and detect abnormal ship behavior, such as approximately elliptical ship loitering trajectories, ship repeated round-trip trajectories, etc.

The analysis and processing of ship trajectory data also lacks a processing method for massive data. The whole process is time-consuming and labor-intensive, and the data processing results lack objectivity and reliability.

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