Date of Award

9-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Department of Aeronautics and Astronautics

First Advisor

William E. Wiesel, PhD

Abstract

The drag acceleration caused by the Earth's atmosphere is a significant cause of prediction uncertainty for low Earth orbit satellites. Most existing research has focused on improving deterministic atmospheric density predictions or on density as a random variable. This research investigates a new paradigm and focuses on modeling the uncertainty caused by air drag using the ballistic coefficient, a component of air drag that is independent of the model used to predict atmospheric density. Time series of ballistic coefficient values were calculated and analyzed as random processes. These random processes were then used as the foundation of a stochastic satellite prediction model that calculates the parameters of the random process and predicts satellite orbits with realistic uncertainty. The model was developed using the Unscented Transform and was validated using Monte Carlo simulation and empirical analysis, and proved effective for any choice of atmospheric density model and for a variety of dynamical formulations.

AFIT Designator

AFIT-ENY-DS-21-S-103

DTIC Accession Number

AD1148773

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Astrodynamics Commons

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