Ship Encounter Situation Recognition by Processing AIS Data from Traffic Intersection Waters

The SVM-BF（Support Vector Machine and Bayesian Filter） are combined to construct the model and algorithm for ship encounter situation recognition. The relative distances and bearings between ships are calculated according to the geometry of ship distribution and defined as the encounter feature set. The feature sequences are fed to the support vector machine to do preliminary classification. The output of the SVM is further processed by the Bayesian filter to make the final results more reliable. The AIS（Automatic Identification System） data from the south channel of the Yangtze estuary is adopted to verify the model and algorithm. The experiments indicate that the recognition model and algorithm can handle typical encounter situations, such as crossing, head-on and overtaking.