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Celestial Bodies Far-Range Detection with Deep-Space CubeSats.
Franzese, Vittorio; Topputo, Francesco.
Afiliação
  • Franzese V; Department of Aerospace Science and Technology, Politecnico di Milano, Via La Masa, 34, 20156 Milano, Italy.
  • Topputo F; Department of Aerospace Science and Technology, Politecnico di Milano, Via La Masa, 34, 20156 Milano, Italy.
Sensors (Basel) ; 23(9)2023 May 07.
Article em En | MEDLINE | ID: mdl-37177748
ABSTRACT
Detecting celestial bodies while in deep-space travel is a critical task for the correct execution of space missions. Major bodies such as planets are bright and therefore easy to observe, while small bodies can be faint and therefore difficult to observe. A critical task for both rendezvous and fly-by missions is to detect asteroid targets, either for relative navigation or for opportunistic observations. Traditional, large spacecraft missions can detect small bodies from far away, owing to the large aperture of the onboard optical cameras. This is not the case for deep-space miniaturized satellites, whose small-aperture cameras pose new challenges in detecting and tracking the line-of-sight directions to small bodies. This paper investigates the celestial bodies far-range detection limits for deep-space CubeSats, suggesting active measures for small bodies detection. The M-ARGO CubeSat mission is considered as the study case for this activity. The analyses show that the detection of small asteroids (with absolute magnitude fainter than 24) is expected to be in the range of 30,000-50,000 km, exploiting typical miniaturized cameras for deep-space CubeSats. Given the limited detection range, this paper recommends to include a zero-phase-angle way point at close range in the mission design phase of asteroid rendezvous missions exploiting deep-space CubeSats to allow detection.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article