Spatio-temporal dp method based on ship trajectory characteristic point extraction

Abstract

A spatio-temporal DP method based on ship trajectory characteristic point extraction, which belongs to the technical field of ship trajectory compression and includes: Step 1: performing clustering analysis on AIS raw data using a clustering algorithm to identify outliers in the AIS data and then eliminate noise points; Step 2: identifying and retaining the characteristic trajectory points of the ship course change, ship speed change, and the ship entering and exiting from a certain area and the like; Step 3: compressing the AIS data by taking the start and end points of the ship trajectory and the characteristic trajectory points retained in step 2 as the initial points, and considering the spatio-temporal characteristics of the AIS data at the same time. The compressed ship can effectively compress redundant AIS data. The compressed ship trajectory has very little difference from the original trajectory, can retain the information of points of the ship motion state change and the points of the ship entering and exiting from the boundary of an area at the same time, has a large reuse value space, and is used for laving the foundation of data processing for ship historical data analysis and ship behavior recognition.