AFRL has performed basic research in Space Situational Awareness (SSA) for many years. With the successful execution of multiple programs during the past two years, AFRL has become the de facto center of mass in the SSA development community. To provide a more complete Defensive Counterspace (DCS) system, AFRLs portfolio of SSA capabilities must be extended to provide Resource Management (RM) functionality. The environmental knowledge provided by SSA is crucial to responding to space threats, but the functionality is not complete without guidance to the operators on how to respond to a dynamic set of adversary activities. ISS proposes to establish a net-centric RM system to dovetail with AFRLs ongoing SSA effort. The Space Threat Objective and Resource Management System (STORM) will provide a parametric optimization RM system based on a distributed genetic algorithm (GA) implementation. An existing User Defined Operating Picture (UDOP) will be updated to provide RM visualization and control. Phase I STORM will integrate with AFRLs Space Situational Awareness Fusion Intelligent Research Environment (SAFIRE) to leverage and enable existing SSA capabilities.
Benefit: STORM will provide an extensible platform for integrating resource management optimization algorithms into a net-centric system. This will allow efficient integration of research-oriented applications into an operational environment. The genetic optimization techniques in STORM will quickly provide courses of action for operators and analysts at JSpOC and other operational space locations. Resource management visualization elements will provide users with the ability to control and monitor the RM optimization process. Commercial applications of STORM include currently envisioned DCS systems such as Space C2, Integrated Space Situational Awareness (ISSA), and the Rapid Attack Identification, Detection, and Reporting System (RAIDRS).
Keywords: Space Situational Awareness, Data Fusion, Resource Management, Net-Centricity, Service Oriented Architecture, Genetic Algorithms
