Service-based extensions to the JDL fusion model

Abstract

Extensions to a previously developed service-based fusion process model are presented. The model accommodates (1) traditional sensor data and human-generated input, (2) streaming and non-streaming data feeds, and (3) the fusion of both physical and non-physical entities. More than a dozen base-level fusion services are identified. These services provide the foundation functional decomposition of levels 0 - 2 in JDL fusion model. Concepts, such as clustering, link analysis and database mining, that have traditionally been only loosely associated with the fusion process, are shown to play key roles within this fusion framework. Additionally, the proposed formulation extends the concepts of tracking and cross-entity association to non-physical entities, as well as supports effective exploitation of a priori and derived context knowledge. Finally, the proposed framework is shown to support set theoretic properties, such as equivalence and transitivity, as well as the development of a pedigree summary metric that characterizes the informational distance between individual fused products and source data.