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Active Decision Support System for Observation Scheduling Based on Image Analysis at the BOROWIEC SLR Station.
Suchodolski, Tomasz.
Afiliação
  • Suchodolski T; Centrum Badan Kosmicznych Polskiej Akademii Nauk (CBK PAN), Bartycka 18A, 00-716 Warszawa, Poland.
Sensors (Basel) ; 22(20)2022 Oct 21.
Article em En | MEDLINE | ID: mdl-36298390
ABSTRACT
The dynamic exploration of the orbits from the LEO-to-GEO region, for the needs of telecommunication services, science, industry and defense, forces monitoring of the trajectory of such orbital objects for the safety of spacecraft traffic and, in the case of deorbitation, for the safety of ground infrastructure. First off all, the need for trajectory monitoring in order to avoid collisions can be distinguished, as well as the need to calibrate the satellite on-board devices. This is mainly carried out by radar measurements, by passive optical acquisition and active laser measurements. The number of orbital objects increases rapidly, and the number of tracking stations for the second is relatively small. This leads to a situation in which each tracking station must select which of the objects will be subject to the measurement task. In the case of the Satellite Laser Ranging (SLR) or passive optical set-up, the weather conditions are an important factor enabling the measurement of the orbital object trajectory. This paper presents an innovative observation scheduling support system based on the analysis of the images obtained from the Allsky camera. The information of the degree of cloud cover, the position of the Sun/Moon in connection with the graphical projections of the ephemeris trajectory of the orbital objects allows increasing the measurement efficiency. The presented solution is part of a larger number of improvements carried out by the author, which lead to the upgrade of SLR stations in terms of new technologies and safety of use.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article