First-Principle Approach to Functionally Decomposing the JDL Fusion Model: Emphasis on Soft Target Data

摘要

The paper summarizes work to date directed at defining a service- based functional decomposition of the fusion process. The resulting architecture accommodates (1) traditional sensor data, as well as human- generated input, (2) streaming and nonstreaming data, and (3) the fusion of both physical and non-physical entities. Fifteen base level fusion services are identified then utilized to construct a service-based decomposition of JDL fusion model levels 0 - 2. 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 framework. A pedigree summary metric is defined that characterizes the informational distance between individual fused products and source data.