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Improved maritime situation awareness by fusing sensor information with intelligence

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Author: Broek, A.C. van den · Deves, T.K.G. · Neef, R.M. · Smith, A.J.E.
Type:article
Date:2010
Institution: TNO Defensie en Veiligheid
Source:6th Global Conference Maritime Systems and Technology - MAST 2010, 9 - 11 November 2010, Rome, Italy
Identifier: 464451
Keywords: Radar · Situational awareness · Maritime environments · Maritime oprations · Littoral environmets · Threat alerts · Information fusing · Sensor fusing · intelligence data

Abstract

In present-day military security operations threats are more difficult to reveal than inconventional warfare theatres, since they take place during the course of normal life. For example, during maritime missions in littoral environments, acts of piracy, drug trafficking and other threatening events become obscured in the crowd of everyday fisheries, cargo traders, ferries and pleasure cruises. By improving the situation awareness threats can be detected more timely and in more detail. We aim to improve situation awareness and threat detection capabilities in maritime scenarios by combining sensor-based information with context information and intelligence from various sources. We use data from radars and electronic warfare sensors on maritime, land-based, airborne and satellite platforms to construct our base operational picture. We enhance this picture by adding intelligence data from AIS sources and from the Lloyds register, and from other sources, such as human observations, open internet databases and past events. Threats can be expressed in patterns of indicators. These indicators are not always directly detectable, but their existence may be revealed by observables: events that are measurable, and that indirectly reveal a threat indicator. For example: the observation that a cargo ship is heading to a harbor other than the destination in the AIS message may hint smuggling. We employ various information analysis and pattern recognition techniques to aggregate the available information into observables and correlate them to threat indicators for automatically producing threat alerts. We demonstrate our concept in a realistic operational maritime scenario