Maritime situational awareness use cases enabled by space-borne sensors

Abstract

This paper discusses a technique for predicting a vessel?s position over a long time horizon with much lower uncertainty than current methods. Lowering the uncertainty of long-range prediction is a key challenge in maritime situational awareness, and in particular for space-based systems can enable data fusion from sensors with different refresh rates, and help optimize the deployment and scheduling of the assets. These tasks are common to several practical scenarios: search and rescue and long-range vessel tracking in sparse data are two main ones. The proposed modelling is compared to one which is widely used in target tracking applications, using terrestrial and satellite Automatic Identification System (AIS) data, and the implications of the improved uncertainty for scenarios relevant to NATO are discussed.