Atmospheric Density Uncertainty Quantification for Satellite Conjunction Assessment

作者: Richard Linares , David J. Gondelach

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摘要: Conjunction assessment requires knowledge of the uncertainty in predicted orbit. Errors atmospheric density are a major source error prediction low Earth orbits. Therefore, accurate estimation and quantification is required. Most models, however, do not provide an estimate density. In this work, we present new approach to quantify uncertainties include these for calculating probability collision Pc. For this, employ recently developed dynamic reduced-order model that enables efficient thermospheric First, used obtain estimates estimates. Second, propagated forward simultaneously with orbit propagation Pc calculation. account effect cross-correlation position due errors on Finally, assessed. The presented provides distinctive capability conjunction while taking into dependence location time. addition, results show it important consider Pc, because ignoring can result severe underestimation probability.

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