The increasing demands of space superiority require a space self defense system with space situation awareness (SSA), or understanding of dynamic events with space assets. Such a system requires sensors to determine the position and velocity of space objects, predict orbits, detect adversary behavior and prevent attacks. IAI and its collaborator, University of New Orleans, propose to apply an advanced game theoretic approach to design a robust, decision-making tool for space self defense systems. A realistic cyber-physical system model will be developed. Then, a dynamic and distributed sensor management algorithm will be developed via a game theoretic approach for maneuver detection and persistent multi-object tracking. Advanced estimation and tracking techniques will be designed by applying nonlinear filters. Finally, a pursuit-evasion game will be designed among all observers and targets to represent their interactions in terms of orbit maneuver behavior and the resulting collision alert for decision support. This approach uses innovative game models to track space objects, analyze their orbits, and provide decision tools for space surveillance systems with self-defense capabilities. It incorporates threat modeling and analysis based on the pursuit-evasion game based active learning of deceptive behavior, nonlinear filters, cooperative sensing for persistent space object tracking by using comprehensive and realistic models of space platforms and service oriented architectures. The proposed framework will be tested via IAI’s wireless network emulation platform RFnestTM with respect to heterogeneous tracking objectives including accuracy, delay, and communication overhead. Supported by the repeatable and scalable experimentation capability of RFnestTM, this approach will facilitate advanced prototyping of effective decision making tools for persistent space self defense systems.