Developments for the Characterization of Spacecraft Proximity Operations for Improved Space Situational Awareness

As space becomes increasingly populated by numerous individuals and organizations, the capabilities of satellites on orbit have also improved. A variety of satellites are able to perform operations in close proximity to each other in order to complete a number of different missions. Maintaining awareness of these operations helps to ensure the continued safe operations in space. This work introduces a method for identifying and characterizing rendezvous and proximity operations (RPO) in space. A Bayesian Belief Network, a probabilistic evaluation tool, is introduced in order to fuse information sources together. Various combinations of relative orbital dynamics, vehicle characteristics, and environmental conditions can be used to determine the potential intent of these close proximity operations. First, a baseline framework is developed to classify the different formations of a satellite trajectory when performing a RPO mission. Sensitivity analyses are introduced in order to understand where the assessment capabilities lose validity as uncertainty is injected into the system. Next, additions to the baseline framework are made to consider specific satellite subsystem characteristics and environmental conditions. The developed framework looks to stand as a proof-of-concept system for information fusion and the characterization of events in the spacecraft domain.