Semantically Enabled Event Reasoning

ABSTRACT: Over the last twenty years the United States has become dependent on space technology for communications, precision tracking and many other applications. Globalization of the worlds economy, which has also dramatically increased over the past twenty years, has resulted in this same dependence in industrialized and developing nations around the world. As a result of these trends, the space domain has become both a contested and congested environment. To maintain United States space superiority, the Joint Space Operations Center (JSpOC) is responsible for tasking the Space Surveillance Network (SSN) and maintaining a catalog of over 22,000 man-made objects. This mission requires innovative technology to aggregate information from distributed, heterogeneous data sources as a means of obtaining Space Situational Awareness (SSA). To meet this technology need, ExoAnalytic Solutions, Inc. proposes to develop Semantically Enable Event Reasoning (SEER). SEER is significant because it uses semantic technology to store information on space objects and automatically discover relationships between space objects and space events. The result is a persistent state of awareness for the space domain. SEER leverages this persistent awareness to build applications that automatically quantify the degradation in space capability to rapidly regain custody of missing satellites. BENEFIT: SEER provides several key contributions to DoD. Most importantly, SEER will provide the JSpOC with a robust Level 2 fusion capability necessary for accomplishing it mission. SEER can also play a valuable systems engineering role within Air Force Space Command (AFSPC). The SEER effort includes the development of an analytical framework for assessing performance of the data fusion algorithms. This framework can be used by systems engineers to help define sensor specifications crucial to SSA and define new SSA quality of service metrics for use by JSpOC. Finally, algorithms and techniques are needed in C4ISR to fuse disparate sensor data for entity disambiguation and uncovering of terrorist networks with little to no a priori knowledge due to rapidly changing techniques of the adversary. SEERs technical approach, the inference algorithms that will be developed, and lessons learned can all be leveraged to further applied research and technology development for data fusion in the C4ISR domain, as well.