Data Fusion Strategies for Automated, Distributed Tracking of Space Objects
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AbstractThe Air Force goal of persistent space situation awareness will be achieved in part by the integrated application of distributed sensors appropriately exploited through advanced methods of fusion and automated analysis. This proposal aims to provide commanders with automated, real-time knowledge-enabled decision making capabilities necessary to avoid direct and observable conflict in space while dominating the space arena utilizing precise information and enhanced and automated decision-making capability. The driving goal of this proposed work is to fully integrate information operations among the various distributed resident space object tracking facilities. This proposal describes a plan to lay the foundation for a system-theoretic approach to fusing space object tracking data from a variety of distributed traditional and non-traditional measurements at both the local and network levels. The basic idea is to first utilize a hierarchical mixture-of-experts architecture regulated by learning networks to fuse the information from multiple sensors and information sources at local tracking stations and to then fuse the information and decisions from these multiple tracking stations at the network level to assess a situation in terms of threat and/or impact in a timely manner. BENEFIT: With precise information and enhanced, automated decision-making capability, commanders can be equipped with the knowledge-enabled decision making capabilities necessary to avoid direct and observable conflict in space while dominating the space arena. The driving goal of this proposed work is to fully integrate information operations among the various distributed resident space object (RSO) tracking facilities in order to fuse intelligence and operations to produce action plans that can be executed in real time. The hierarchical mixture-of-experts architecture and algorithms fuse information from multiple sensors and sources of information at local tracking stations and then fuse information and decisions from multiple tracking stations at a network level to assess a situation in terms of threat and/or impact in a timely manner. The architecture and algorithms developed during Phase 2 will be developed into a software product that could be incorporated into Analytical Graphic, Inc. (AGI)'s Orbit Determination Toolkit (ODTK) as an add-on module or integrated into a Service Oriented Architecture (SOA) based ground system. This product could then be integrated into the Joint Space Operations Center (JSpOC) Mission System (JMS). Incorporating this software into ODTK as an add-on module would enable Emergent Space Technologies, Inc. to leverage the sales and marketing infrastructure of AGI to provide the widest possible dissemination and usage of the technology developed under this SBIR.
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