Open AccessA Framework to Estimate Local Atmospheric Densities With Reduced Drag‐Coefficient Biases
Author(s) -
Ray Vishal,
Scheeres Daniel J.,
Alnaqbi Suood,
Tobiska W. Kent,
Hesar Siamak G.
Publication year - 2022
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1029/2021sw002972
Subject(s) - drag , drag coefficient , satellite , environmental science , density of air , atmosphere (unit) , atmospheric models , orbit determination , computational physics , remote sensing , meteorology , inversion (geology) , atmospheric sciences , physics , geodesy , mechanics , geology , paleontology , structural basin , astronomy
An accurate estimation of upper atmospheric densities is crucial for precise orbit determination (POD), prediction of low Earth orbit satellites, and scientific studies of the Earth's atmosphere. But densities estimated using satellite tracking data are always uncertain up to the drag‐coefficient assumed in the inversion method. This work develops a new framework to simultaneously estimate the density and drag‐coefficient for satellites with a time‐varying attitude. We do so by leveraging Fourier drag‐coefficient models, previously developed by the authors, and physical models of the drag‐coefficient. The method is tested with synthetic data for different geomagnetic activities, altitude levels, and errors in the gas‐surface interaction parameters. We report an improvement of up to 70% in density estimates for the simulations. Finally, POD data from Spire satellites are used for validation. An improvement of around 29% is obtained in the filter density estimates over NRLMSISE‐00 and 49% over JB2008 compared to the High Accuracy Satellite Drag Model densities.