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.