Multi-fidelity orbit uncertainty propagation

Abstract

To reduce computation time while limiting loss in accuracy when propagating an orbit state probability density function, this work seeks to develop an adaptive approach to multi-fidelity uncertainty propagation for applications in astrodynamics. Using the method of stochastic collocation, a set of particles produced via a low-fidelity solver defines a basis used in the surrogate over the space of propagated states. This basis allows for identifying a subset of important samples that are re-propagated using a high-fidelity propagator, which defines a correction for the original basis. This approach reduces computation time for propagating a particle ensemble or a Gaussian mixture model via the unscented transform. This paper demonstrates the efficacy of this method for several Earth-orbit test cases, and provides a means for merging general and special perturbation theories to produce a posterior probability density function more statistically consistent with a precise estimated state.