Defensive Counterspace (DCS) and Space Situational Awareness (SSA) Resource Management using Artificial Intelligence Techniques

Managing the resources and responses to DCS situations is a large, complex problem.  We have developed an innovative planning and resource optimization system architecture which facilitates the development of more intelligent, optimizing resource management algorithms.  It has been applied to NASA Ground Network (space communications) scheduling and several domains including those involving similarly complex constraints, such as the problem of optimizing ballistic missile engagements which includes complex line of sight (LOS) and range calculations between satellite-based sensors and three-dimensional ballistic missile trajectories.  The innovation is to apply that expertise, the planning and resource management architecture, and a new domain-independent algorithm, to the problem of planning and optimizing DCS responses and SSA sensors. The ultimate goal of this proposed effort is to improve DCS/SSA response and resource management.  The goals of the Phase I research are to understand the current and future DCS/SSA resource management domain, investigate integration requirements, elaborate the heuristics, algorithms and techniques for improved DCS/SSA resource management, analyze them as to their feasibility, define the metrics for planning performance, further prove the feasibility through prototype development, and develop the Phase II system design. BENEFIT: The most direct target for the results of this effort is, of course, the Air Force''''''''s DCS/SSA resource management domain, itself.  By both demonstrating significantly improved performance during Phase II and ensuring that the ultimate results can be operationalized, the Air Force will have a strong incentive to transition the Phase II development of the proposed Resource Manager.  There are many similarities between SSA sensor resource management and satellite communication scheduling.  So the Space Communication Networks (AFSCN, DSN, GN, and SN) could all benefit from this technology.  The algorithms developed here could be marketed to our existing Air Force and Navy sensor customers interested in sensor resource management and coordination.  We are already marketing Aurora, our general intelligent planning and scheduling framework, and customizing it for a variety of domains.  The additional capabilities developed for DCS/SSA resource management can be synergistically marketed to the same clients.