SBIR-STTR Award

The potential disinteroperabilities and inefficiencies of current fusion architectures can be mitigated in a number of ways including reduced, coordinated, and standardized coupling of components. This proposal is for an ontology-based fusion architecture that will enable fusion agents to operate in independent, yet coordinated, manners. It is based on recent research in the area of ontology-based fusion in the international fusion community. Yet we will show how the approach is also well-grounded in actual DoD fusion systems and algorithms experience, indeed the idea of an ontology-based fusion resulted from many years of fusion project experience. What is planned for the Phase 1 effort is two parallel tracks, (1) develop the theory of ontology networks as a basis for inference; and (2) proof-of-concept demonstrations of the efficacy of the approach. For the proof-of-concept demonstrations, we plan scaled down experiment to verify the feasibility of independent fusion modules (inferlets) to operate within an spreading activation network based on an ontology. We will use a subset of the C2 Core ontology to support experimentation with already-developed algorithms for, (1) tracking filters, (2) association and assignment, and, if the Phase 1 option is exercised, (3) ESM/ELINT classification and identification.

Keywords:
Fusion, Ontology, Inference, Open Architecture

This project is for an open architecture for fusion algorithms that lays a foundation for future advanced inference, particularly fusion inference. This architecture will enable more extensive data fusion such as non-kinematic level 1 fusion, level 2 and 3 complex assessments, broader scope of Situation Awareness and Battle Management information, and level 4 adaptation. It enables higher quality data fusion through enforced integrity of integrated data responsive to an open ontology and through the ability for multiple kinds of fusion algorithms to interoperate autonomously yet synergistically. This proposal is to continue advancing the theory and implementation of this exciting and promising new architecture. Now that we are satisfied with the loading of the implemented ontology and have some insight into rehosting actual fusion algorithms into the architecture, we need to experiment with integrating into the AHE mission environment and conforming existing and emerging AHE fusion software to the architecture (e.g., the MSI, CID, and ATO correlator software),. Concurrently, we propose to continue developing the logic and mathematics of ontologic inference networks so the architecture will be ready to support even more advanced fusion levels in the future.

Keywords:
Fusion, open architecture, automated reasoning, inference, ontology