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Joint determination of Venus gravity and atmospheric density through EnVision radio science investigation.

Authors :
Gargiulo, Anna Maria
Genova, Antonio
Petricca, Flavio
Del Vecchio, Edoardo
Andolfo, Simone
Torrini, Tommaso
Rosenblatt, Pascal
Lebonnois, Sébastien
Marty, Jean-Charles
Dumoulin, Caroline
Source :
Acta Astronautica. Feb2024, Vol. 215, p725-738. 14p.
Publication Year :
2024

Abstract

The ESA mission EnVision will address its main scientific questions through a detailed mapping of the surface and interior properties of Venus. A precise reconstruction of the spacecraft trajectory is a key requirement for the EnVision scientific investigations, including radio science. To precisely constrain the orbit evolution, refined models of the dynamical forces are included in the Precise Orbit Determination (POD) process. We developed a methodology based on a batch-sequential filter that enables a joint estimation of Venus gravity and atmospheric density. Our approach yields an accurate compensation of atmospheric mismodeling, simulated through semi-empirical predictions of the atmospheric density provided by general circulation models (GCM), e.g. , Venus Climate Database (VCD). Numerical simulations of the EnVision radio science investigation were carried out by using a perturbative analysis of the dynamical forces, which accounts for atmospheric density errors ≥ 200%. By adjusting a set of atmospheric scale factors, our proposed strategy enables an estimation of the atmospheric density at the spacecraft altitudes with an accuracy of 25%. The improved dynamical model yields accuracies in the orbit reconstruction of 1–2 m, 30–40 m and 20–30 m in the radial, transverse and normal directions. • We present an enhanced approach for the precise orbit determination of the ESA EnVision mission. • Our method enables a joint determination of Venus' gravity and atmospheric density. • We discuss a thorough analysis of uncompensated atmospheric drag mismodeling. • The retrieved atmospheric scale factors are used to correct Venus' atmospheric model predictions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00945765
Volume :
215
Database :
Academic Search Index
Journal :
Acta Astronautica
Publication Type :
Academic Journal
Accession number :
174916420
Full Text :
https://doi.org/10.1016/j.actaastro.2023.12.010