Targeting and image acquisition of Martian surface features with TGO/CaSSIS
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Author
Almeida, M.Read, M.
Thomas, N.
Cremonese, G.
Becerra, P.
Borrini, G.
Byrne, S.
Gruber, M.
Heyd, R.
Marriner, C.M.
McArthur, G.
McEwen, A.S.
Pommerol, A.
Perry, J.
Schaller, C.
Affiliation
Lunar and Planetary Laboratory, University of ArizonaIssue Date
2023-07
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Elsevier LtdCitation
Almeida, M., Read, M., Thomas, N., Cremonese, G., Becerra, P., Borrini, G., ... & Schaller, C. (2023). Targeting and image acquisition of Martian surface features with TGO/CaSSIS. Planetary and space science, 231, 105697.Journal
Planetary and Space ScienceRights
© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
CaSSIS is a high-resolution visual telescope onboard the ExoMars Trace Gas Orbiter. The mission started the primary science phase in April 2018. The relatively small single image footprint (typically 40 km × 9.5 km) when compared to the total surface area of Mars demands that images should be targeted and target selection is key for the science return. This paper describes the science planning concept set around the target selection, and the process followed in order to generate the CaSSIS commands. The tools used are described as well as all the iterations and teams involved. Finally, special cases and the handling of contingencies are discussed. The procedures may serve as a guideline for future high-resolution instruments on missions to planetary objects. © 2023 The AuthorsNote
Open access articleISSN
0032-0633Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1016/j.pss.2023.105697
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Except where otherwise noted, this item's license is described as © 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).