Propagation and reconstruction of re-entry uncertainties using continuity equation and simplicial interpolation

TL;DR

This paper introduces a continuum-based method combining the continuity equation and simplicial interpolation to efficiently propagate and reconstruct uncertainties in spacecraft re-entry predictions, offering a promising alternative to Monte Carlo simulations.

Contribution

The work presents a novel approach that uses the continuity equation and gradient-enhanced linear interpolation for uncertainty propagation and reconstruction in re-entry dynamics.

Findings

The method accurately reconstructs probability distributions compared to Monte Carlo.

It reduces computational runtime significantly for the tested cases.

Effective in handling uncertainties in initial conditions and parameters.

Abstract

This work proposes a continuum-based approach for the propagation of uncertainties in the initial conditions and parameters for the analysis and prediction of spacecraft re-entries. Using the continuity equation together with the re-entry dynamics, the joint probability distribution of the uncertainties is propagated in time for specific sampled points. At each time instant, the joint probability distribution function is then reconstructed from the scattered data using a gradient-enhanced linear interpolation based on a simplicial representation of the state space. Uncertainties in the initial conditions at re-entry and in the ballistic coefficient for three representative test cases are considered: a three-state and a six-state steep Earth re-entry and a six-state unguided lifting entry at Mars. The paper shows the comparison of the proposed method with Monte Carlo based techniques in terms of quality of the obtained marginal distributions and runtime as a function of the number of samples used.