Association in Level 2 fusion

After a number of years of intensive research on Level 1 fusion, the focus is shifting to higher levels. Level 2 fusion differs from Level 1 fusion in its emphasis on relations among objects rather than on the characteristics (position, velocity, type) of single objects. While the number of such characteristics grows linearly with the number of objects considered by an information fusion system, this cannot be said about the number of possible relations, which can grow exponentially. To alleviate the problems of computational complexity in Level 2 processing, the authors of this paper have suggested the use of ontologies. In this paper we analyze the issue of association in Level 2 fusion. In particular, we investigate ways in which the use of ontologies and annotations of situations in terms of the ontologies can be used for deciding which of the objects, and/or relations among such, can be considered to be the same. This is analogous to data association in Level 1 fusion. First, we show the kinds of reasoning that can be carried out on the annotations in order to identify various objects and possible coreferences. Second, we analyze how uncertainty information can be incorporated into the process. The reasoning aspect depends on the features of the ontology representation language used. We focus on OWL - the web ontology language. This language comprises, among others, constructs related to expressing multiplicity constraints as well as such features like “functional property” and “inverse functional property”. We will show how these features can be used in resolving the identities of objects and relations. Moreover, we will show how a consistency-checking tool (ConsVISor) developed by the authors can be used in this process.