Toward Improved Physics-Based Simulations of the LEO Space Environment
using GNSS-Enabled Small Satellites
Abstract
Satellite-atmosphere interactions cause large uncertainties in low-Earth
orbit determination and prediction. Thus, knowledge of and the ability
to predict the space environment, most notably thermospheric mass
density, are essential for operating satellites in this domain. Recent
progress has been made toward supplanting the existing empirical,
operational methods with physics-based data-assimilative models by
accounting for the complex relationship between external drivers and
their response in the upper atmosphere. Simultaneously, a new era of
CubeSat constellations is set to provide data with which to calibrate
our upper-atmosphere models at higher resolution and cadence. With this
in mind, we provide an initial method for converting precision orbit
determination (POD) solutions from global navigation satellite system
(GNSS) enabled CubeSats into timeseries of thermospheric mass density.
This information is then fused with a physics-based, data-assimilative
technique to provide calibrated global densities.