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Dell'Elce L.,University of Liège | Dell'Elce L.,Space Structures and Systems Laboratory | Kerschen G.,University of Liège | Kerschen G.,Space Structures and Systems Laboratory
Journal of Guidance, Control, and Dynamics | Year: 2015

This paper is devoted to the probabilistic uncertainty quantification of orbital lifetime estimation of low-altitude satellites. Specifically, given a detailed characterization ofthe dominant sourcesof uncertainty, wemap this input into a probabilistic characterization of the orbital lifetime through orbital propagation. Standard Monte Carlo propagation is first considered. The concept of drag correction is then introduced to facilitate the use of polynomial chaos expansions and to make uncertainty propagation computationally effective. Finally, the obtained probabilistic model is exploited to carry out stochastic sensitivity analyses, which in turn allow gaining insight into the impact uncertainties have on orbital lifetime. The proposed developments are illustrated using one Cube Sat of the QB50 constellation.


Dell'Elce L.,University of Liège | Dell'Elce L.,Space Structures and Systems Laboratory | Arnst M.,University of Liège | Arnst M.,Space Structures and Systems Laboratory | And 2 more authors.
Journal of Guidance, Control, and Dynamics | Year: 2015

Orbital lifetime estimation is a problem of great timeliness and importance in astrodynamics. In view of the stochastic nature of the thermosphere and of the complexity of drag modeling, any deterministic assessmentof orbital lifetime is likely to be bound to failure. This is why the present paper performs uncertainty quantification of satellite orbital lifetime estimation. Specifically, this paper focuses on the probabilistic characterization of the dominant sources of uncertainty inherent to low-altitude satellites. Uncertainties in the initial state of the satellite and in the atmospheric drag force, as well as uncertainties introduced by modeling limitations associated with atmospheric density models, are considered. Mathematical statistics methods, in conjunction with mechanical modeling considerations, are used to infer the probabilistic characterization of these uncertainties from experimental data and atmospheric density models. This characterization step facilitates the application of uncertainty propagation and sensitivity analysis methods, which in turn allows gaining insight into the impact that these uncertainties have on the orbital lifetime. The proposed developments are illustrated using one Cube Sat of the QB50 constellation. Copyright © 2014bythe American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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