Atmospheric Density Estimation Techniques for Aerocapture

Abstract

Aerocapture is a promising orbit insertion strategy that can reduce propellant mass requirements for planetary orbiters. Reliable aerocapture requires active guidance, navigation, and control systems for robust performance. Such systems rely on accurate models of the downstream density environment for accurate targeting capabilities. Two density profile prediction techniques are introduced that use density histories computed from navigation measurements to improve aerocapture targeting accuracy: the density interpolator and the ensemble correlation filter. The density interpolator stores density data on the descent portion of the vehicle’s trajectory, interpolating density values from this array during guidance predictions; whereas the ensemble correlation filter attempts to match density history data to onboard density profiles. A hybrid of the two methods is also considered. Both Earth and Venus are considered as planetary targets. A discrete-event control aerocapture scenario is considered, using Monte Carlo methods to assess the proposed methods’ performances and demonstrate improvement in both the apoapsis error and entry corridor width. Density interpolator strategies were shown to perform consistently better than the density scale factor approaches. Ensemble correlation strategies were shown to provide a larger performance benefit potential as compared to interpolator strategies, particularly in cases where density model confidence is high. However, density interpolator strategies were shown to improve performance over a wider range of Monte Carlo simulation conditions.