Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization
Coder, Ryan Daniel
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Recognizing the increasingly congested and contested nature of space, this thesis contends that the fusion of small aperture, autonomous telescopes with Bayesian inference techniques can provide timely, actionable evidence of specific threats and hazards to space based assets. This evidence is required for a robust, persistent Space Domain Awareness capability that decision makers can employ to protect space services and capabilities. A multi-objective design framework for optical systems is defined empowering designers to identify families of designs which represent feasible solutions to user specific Space Domain Awareness mission requirements. Several trade studies are presented, the outputs of which directly inform the construction of the Georgia Tech Space Object Research Telescope. Novel techniques which ingest the unresolved imagery provided by small telescopes are developed, affording the estimation of attitude and angular velocity states of maneuvering space objects without prior knowledge of initial attitude, while maintaining computational tractability. Statistical inference techniques are applied to these posterior state distributions to rank the hypothesized subjects most likely under surveillance by the maneuvering space object in terms of their stochastic dominance. The totality of these contributions is validated on experimentally collected measurements of the Hubble Space Telescope.