A Formal Semantic Framework for Maritime Situation Analysis

Situation analysis is a process of examining a situation to provide and maintain a state of situation awareness which is critical for dynamic decision-making in responding to real-world situations. Limited surveillance resources constrain maritime domain awareness and compromise safety and security coverage at all times. This calls for innovative intelligent systems for interactive situation analysis to assist marine authorities in their routine surveillance operations. In this research, we use the Abstract State Machine method to formally model and design a precise yet concise situation analysis framework. The backbone of our model is an existing abstract framework. We expand and enrich it by capturing detailed requirements and specifying the precise behavior of its components to process, analyze, and fuse large volumes of marine traffic data received from various sources. To this end, we propose a time series structure for rendering vessel trajectories from real-time data.