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Game-Theoretic based Decision Support Tools for Persistent Space Denial

Description:

OBJECTIVE: Develop new game decision models and efficient computational algorithms for autonomous space systems with the capabilities for self defense when there are potential adversarial strikes. DESCRIPTION: Former Air Force Space Command (AFSPC) Commander General Lance Lord defined space situation awareness (SSA) in simple terms:"The foundation of Space Superiority is Space Situation Awareness, which means having a complete understanding of what is happening in space."What exactly does this mean? General Lord goes on to say in his 2005 article in High Frontier that"It is no longer sufficient to simply know where a satellite is in space. We must know what the satellite is capable of doing, what it is being used for and what it may be used for in the future."Today the United States has a tremendous investment in space, especially in military, intelligence, scientific, and commercial sectors. However, one of the most important space vulnerabilities is the lack of persistent situation awareness of the space operational environment to ensure freedom of action. Space can be an important battlefield in modern warfare because intelligence information from the space has become extremely vital for strategic decisions. The presence of adversaries in addition to real-time and hidden information constraints greatly complicates the decision making process. It becomes necessary to perform space defense analysis and mission trade studies. Although pursuit-evasion game theory is relevant to this problem, most results in the existing literature are from the pursuers"perspective and thus not applicable. Innovative solutions are sought for (a) proper game models and constructive game training for a space-based Low Earth Orbit (LEO) and/or near Geostationary Earth Orbit (GEO) defending scenario whereby multiple denying LEO/near GEO assets, defending LEO/near GEO assets and pursuing LEO/near GEO assets with either equal or unequal capabilities are assumed with imperfect, sporadic observations and jamming confrontations due to dynamic network topologies and inter-satellite links (ISLs); (b) possible constructive methods and approximate solution techniques on distributed learning under sparse communications and adverse environments due to orbital geometries, propagations and interferences; (c) efficient computational algorithms to determines real-time cooperative strategies for LEO/near GEO assets, neutral objects and threats in persistent area denial; and (d) assess the performance under technical failure inaccurate measurements and loss of communications. Proposed advances together with potential deliverables including novel mathematical developments, interaction modeling, performance metrics, advanced engagement concepts, and design principles shall set the foundations to enable assured operations of teams of autonomous defense systems to adapt to hostile and non-traditional environments which shall capitalize on effective utilization of modeling and analysis of uncertain systems as well as multi-level, multi-group, multi-agent control and decision analysis. PHASE I: Develop constructive methods and analysis tools for a proof-of-concept entailing orbital geometries of LEO and/or near GEO assets, antenna beamwidths, crosslink angular velocities, ISL interferences, Doppler shifts and adversarial engagements including co-orbital threat models, levels of deception and collateral damages, asymmetric sensing and actuation capabilities for LEO and/or near GEO assets. PHASE II: Refine Phase I system concept and algorithms of the proof-of-concept to include operational constraints of space-based visible/radar sensors, LEO/near GEO space platforms, maneuver capabilities, characteristics of orbital planes and space assets per plane on asset observability and reachability. Conduct 3D simulations and visualizations to characterize performance of decision support tools using NASA General Mission Analysis, OMNET++, Java programming, Service-Oriented-Architecture framework. PHASE III: Adversarial decision analysis and robust decision making tools from Phase II activities are applicable to protected tactical space communications with dynamic spectrum sharing, routing adaptation and interference mitigations. REFERENCES: 1. Gen Lance Lord,"Space Superiority,"High Frontier 1, No. 3 (2005):4. 2. D. Li, J.B. Cruz, Jr., and C. Schumacher,"Stochastic Multi-Player Pursuit Evasion Differential Games,"International Journal of Robust and Nonlinear Control, Vol. 18, pp. 218247, 2008. 3. K. D. Pham,"Risk-Averse Based Paradigms for Uncertainty Forecast and Management in Differential Games of Persistent Disruptions and Denials,"Proceedings of American Control Conference, pp. 842-849, Baltimore, MD, 2010. 4. D. Shen, K. D. Pham, G. Chen and E. P. Blasch,"Pursuit-Evasion Orbital Game for Satellite Interception and Collision Avoidance,"SPIE Defense and Security 2011: Sensors and Systems for Space Applications IV, Proceedings of SPIE, Vol. 8044, Orlando, FL, 2011.
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