Semantically Enabled Event Reasoning

ABSTRACT: Over the past twenty years, the United States and other nations around the world have become dependent on space technology for communications, precision tracking and many other applications, causing the space domain to become both contested and congested. To maintain Unites States space superiority, the Joint Space Operations Center (JSpOC) is responsible for tasking the Space Surveillance Network (SSN) and maintaining a catalog of more than 22,000 man-made objects. This mission requires innovative technology to aggregate information from distributed, heterogeneous data sources to obtain Space Situational Awareness (SSA). To meet this technology need, ExoAnalytic Solutions, Inc. proposes to develop Semantically Enabled Event Reasoning (SEER) for the space domain. The objectives of SEER are: 1) to develop multi-sensor data fusion algorithms for correlating space events across heterogeneous data sources; 2) to develop a relationship estimation algorithm based on correlated space events; 3) to provide context for the estimated relationships; and 4) to develop an analytical framework for assessing performance of SSA Level 2 fusion algorithms. 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 its mission. SEER can also play a valuable systems engineering role within Air Force Space Command (AFSPC). The SEER effort includes developing a performance assessment framework for 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 for uncovering terrorist networks with little to no a priori knowledge due to the adversary"s rapidly changing techniques. SEER"s technical approach, the inference algorithms that will be developed, and lessons learned, can also be leveraged to further applied research and technology development for data fusion in the C4ISR domain.