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Atmospheric density is the most important factor for accurate estimation of the drag force exerted on spacecraft at Low Earth orbits. Empirical models provide the most accurate estimation of the density currently available, although they still suffer from estimation errors. This work presents a novel approach based on Neural Networks for reducing the error in the density estimated by empirical models,...
At low Earth orbits, drag force is a significant source of error for propagating the motion of a spacecraft. The main factor driving the changes on the drag force is neutral density. Global atmospheric models provide estimates for the density which are significantly affected by bias due to misrepresentations of the underlying physics and limitations on the statistical models. In this work a localized...
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