Applying Knowledge-Based Reasoning for Information Fusion in Intelligence, Surveillance, and Reconnaissance

In this study, an information fusion component is presented, designed for fusing information acquired by a distributed surveillance system with prior information contained in intelligence databases. The fusion component is part of a larger system supporting the situational awareness of operators and decision makers in military and civil security domains based on concepts and processes in ISR (Intelligence, Surveillance and Reconnaissance). The distributed surveillance system is composed of unmanned aircraft systems, acquiring sensor data which has to be integrated with background information for providing useful input to a situational picture. To this end, the information fusion component includes mechanisms for information integration and conclusion drawing, based on an expressive knowledge model and on employing different reasoning techniques. This paper constitutes an extended version of [1], including further details on knowledge modeling, information extraction and model transformations as well as a first concept for an agent-based realization of the fusion system.