Using ontologies and symbolic information in automatic target recognition

The goal of this paper is to show an approach to target recognition (ATR) that allows for efficient updating of the recognition algorithm of a fusion agent when new symbolic information becomes available. This information may, for instance, provide additional characterization of a known type of target, or supply a description of a new type of target. The new symbolic information can be either posted on a web page or provided by another agent. The sensory information can be obtained from two imaging sensors. In our scenario the fusion agent, after noticing such an event, processes the new symbolic information and incorporates it into its recognition rules. To achieve this goal the fusion agent needs to understand the symbolic information. This capability is achieved through the use of an ontology. Both the fusion agent and the knowledge provider (it may be another software agent or a human annotator) know the ontology, and the web based information is annotated using that ontology. In this paper we describe the approach, provide examples of symbolic target descriptions, describe an ATR scenario, and show some initial results of simulations for the selected scenario. The discussion in this paper shows the advantages of the proposed approach over that in which the recognition algorithm is fixed.