Higher-Order Tensor-Based Deferral of Gaussian Splitting for Orbit Uncertainty Propagation
G. Andrew Siciliano, Keith A. LeGrand, Jackson Kulik

TL;DR
This paper presents a higher-order tensor-based deferred splitting method for Gaussian mixture uncertainty propagation in orbital dynamics, improving computational efficiency and accuracy in complex space scenarios.
Contribution
It introduces a novel deferred splitting algorithm integrated with higher-order techniques, enhancing efficiency and accuracy in orbital uncertainty propagation.
Findings
Substantial computational savings with maintained accuracy.
Second-order moments improve propagation precision.
Effective across diverse orbital regimes.
Abstract
Accurate propagation of orbital uncertainty is essential for a range of applications within space domain awareness. Adaptive Gaussian mixture-based approaches offer tractable nonlinear uncertainty propagation through splitting mixands to increase resolution in areas of stronger nonlinearities, as well as by reducing mixands to prevent unnecessary computational effort. Recent work introduced principled heuristics that incorporate information from the system dynamics and initial uncertainty to determine optimal directions for splitting. This paper develops adaptive uncertainty propagation methods based on these robust splitting techniques. A deferred splitting algorithm tightly integrated with higher-order splitting techniques is proposed and shown to offer substantial gains in computational efficiency without sacrificing accuracy. Second-order propagation of mixand moments is also seen…
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Taxonomy
TopicsSpacecraft Dynamics and Control · Space Satellite Systems and Control · Tensor decomposition and applications
