Radar/AIS data fusion and SAR tasking for Maritime Surveillance

Abstract

Numerous national and multinational initiatives in maritime surveillance have been initiated, with the goal of having knowledge of all coastal and open-seas activities relevant to national security. As part of this effort, NATO is pursuing research activities to exploit existing multi-sensor systems in support of maritime surveillance. Multi-sensor fusion of data from maritime surveillance assets provides a consolidated surveillance picture for anomaly detection. This paper develops a model for multisensor fusion and Bayesian anomaly detection that quantifies the value of sensor data for maritime surveillance performance. An approach to satellite imagery tasking for optimal surveillance performance is also given. Simulation results corroborate our analysis.