2022
DOI: 10.1109/tns.2022.3153081
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Infer Electron Space Environment Along EOR Mission Profile From LEO Measurements: Application to EUTELSAT 7C

Abstract: The Earth's electron radiation environment is extremely dynamic. It reacts strongly to magnetic storms, increasing in some hours by several orders of magnitude in a large energy range, and decreasing slowly in the recovery phase of the storm. For the purpose of spacecraft Electrical Orbit Raising, to bring the ion thruster propulsion based satellites from the launcher injection orbit to the geostationary orbit, it is important to estimate the electron fluxes they can encounter during this long transfer phase. … Show more

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Cited by 2 publications
(2 citation statements)
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“…This phenomenon gave rise to the presence of so-called "killer electrons" which are capable of penetrating even lunar surfaces. Moreover, these killer electrons deposit charge within the medium, introducing a certain likelihood of charge-discharge effects that pose a threat to satellite safety and the overall reliability of space missions [15][16][17][18].…”
Section: Effects Of Geomagnetic Storm and High-energy Electron Storm ...mentioning
confidence: 99%
“…This phenomenon gave rise to the presence of so-called "killer electrons" which are capable of penetrating even lunar surfaces. Moreover, these killer electrons deposit charge within the medium, introducing a certain likelihood of charge-discharge effects that pose a threat to satellite safety and the overall reliability of space missions [15][16][17][18].…”
Section: Effects Of Geomagnetic Storm and High-energy Electron Storm ...mentioning
confidence: 99%
“…One example is MERLIN (Smirnov et al., 2020), which uses machine learning to nowcast the electron flux at MEO from the Combined X‐ray dosimeter (CXD) measurements on the GPS constellation (Morley et al., 2017) based on solar wind and geomagnetic indices. Another approach is to utilize the global coherence between LEO measurements and the environment at higher orbits (Chen et al., 2016; Kanekal et al., 2001; Lazaro et al., 2022) to map between the two altitudes. Recently, many models have been developed using this coherence, including Pre‐MevE (Chen et al., 2019; Pires de Lima et al., 2020; Sinha et al., 2021), and the SHELLS model (Claudepierre & O’Brien, 2020).…”
Section: Introductionmentioning
confidence: 99%