RESOURCE-CONSTRAINED AUTONOMOUS OPERATIONS OF SATELLITE CONSTELLATIONS AND GROUND STATION NETWORKS
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Authors
Minelli, Giovanni
Subjects
optimization
CubeSat
mission operations
MC3
Gaussian targeting
benefit value function
dynamic optimization
DIDO
CubeSat
mission operations
MC3
Gaussian targeting
benefit value function
dynamic optimization
DIDO
Advisors
Ross, Isaac M.
Romano, Marcello
Giraldo, Francis X.
Newman, James H.
Karpenko, Mark
Date of Issue
2018-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
To address the growing population of small satellite constellations that rely on distributed ground station networks, a dynamic optimization problem is formulated and solved. Specifically, this dissertation addresses the problem formulation, algorithm implementation, and experimental techniques developed to optimally slew ground-based antennas between multiple satellites that are simultaneously in view of one or more earth stations. The problem is solved using DIDO, a MATLAB optimal control solver, to produce deconflicted ground antenna slew trajectories. The deconfliction parameters include space-to-ground link budgets, mission priority, asset availability, and onboard health. Traditional methods employ heuristics to generate a subset of available targets and a separate process to check feasibility of the solution. The method described in this dissertation deterministically solves the problem in a single step. The approach is experimentally validated and tested using a small constellation of low-Earth-orbiting CubeSats operated by the Small Satellite Laboratory at the Naval Postgraduate School, using the Mobile CubeSat Command and Control (MC3) ground station network.
Type
Thesis
Description
Series/Report No
Department
Mechanical and Aerospace Engineering (MAE)
Organization
Identifiers
NPS Report Number
Sponsors
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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Copyright is reserved by the copyright owner.