This invention discloses an abnormal behavior detection method for ships based on an ADS-B
big data platform, specifically relating to the field of ship
navigation safety monitoring technology. The method involves acquiring automatic correlation surveillance
broadcast data of ships in a target sea area, constructing a ship trajectory evolution matrix, and generating a ship micro-disturbance motion feature
tensor. It also involves constructing a ship neighborhood interaction topology network and calculating the trajectory disturbance propagation weights between nodes to form an abnormal propagation probability matrix. Furthermore, it establishes a
coupling response relationship between the local trajectory disturbance energy sequence and the neighborhood interaction intensity through temporal folding mapping, generating an abnormal behavior evolution prediction curve and calculating an abnormal energy aggregation index. Combined with the abnormal propagation probability matrix, it generates a
risk distribution map of abnormal ship behavior, extracts implicit behavior indicators, and dynamically matches them with preset abnormal behavior patterns. This invention can effectively identify micro-scale abnormal navigation behavior in complex sea environments, improving the accuracy of abnormal ship behavior detection and early warning capabilities.