Abstract: In order to accurately extract ship's encountering situation, spatial and temporal analysis of AIS data from the south channel of the Yangtze river estuary was carried out, and an automatic extraction method for the encountering situation of ships based on pattern classification was proposed. Firstly, the spatio-temporal constraint conditions in the encounter process were used to extract the ship matching information. Then encounter trajectory was synchronized by data interpolation, and encounter scene was reconstructed. Finally, spatio-temporal evolution characteristics of ship encountering were analyzed, and relative distance and course difference features in a specific time window were extracted to form encounter feature sequence. SVM algorithm was used to classify and identify the encounter feature sequence to realize the automatic extraction of encounter situation. The results show that setting spatio-temporal constraints can accurately extract ship pairing trajectory information, that the spatio-temporal analysis of encounter process can reconstruct encounter scene, and that the accuracy rate of the encounter situation extraction algorithm designed by SVM is over 90%, which reduces the misjudgment rate compared with traditional methods.

Key words: ship encounter situation, automatic identification system(AIS), spatiotemporal analysis, support vector machine(SVM), automatic extraction