Date of Award:

5-2022

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Mechanical and Aerospace Engineering

Committee Chair(s)

David K. Geller

Committee

David K. Geller

Committee

Stephen A. Whitmore

Committee

Matthew W. Harris

Committee

Geordie Richards

Committee

Randall Christensen

Abstract

Rendezvous and proximity operations for automated spacecraft systems requires advanced path planning techniques that are capable of generating optimal paths. Real-world constraints, such as sensor noise and actuator errors, complicate the planning process. Operations also require flight safety considerations in order to prevent the spacecraft from potentially colliding with the associated companion spacecraft. This work proposes a new, ground-based trajectory planning approach that seeks an optimal trajectory while meeting all mission constraints and accounting for vehicle performance and safety requirements. This approach uses a closed-loop linear covariance simulation of the relative trajectory coupled with a genetic algorithm to determine fuel optimal trajectories. Spacecraft safety is addressed using statistical data from the linear covariance model to bound the probability of collision.

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