GEO region; Iterative proportional fitting method; Microsimulation; Space debris; Synthetic population; Modeling and Simulation; Mathematical Physics; Astronomy and Astrophysics; Space and Planetary Science; Computational Mathematics; Applied Mathematics
Abstract :
[en] The number of space debris has increased in the orbital environment, and consequently, the risk of collision between satellites and space debris or space debris and space debris has become a hot topic in Celestial Mechanics. Unfortunately, just a small fraction of the biggest and brightest objects are visible by means of radar and optical telescopes. In the last years, many efforts have been made to simulate the creation of space debris populations through different models, which use different sources and diverse orbital propagators, to study how they evolve in the near future. Modeling a fragmentation event is rather complex; furthermore, large uncertainties appear in the number of created fragments, the ejection directions and velocities. In this paper, we propose an innovative way to create a synthetic population of space debris from simulated data, which are constrained by observational data, plus an iterative proportional fitting method to adjust the simulated population by statistical means. The final purpose consists in improving a synthetic population of space debris created with a space debris model helped by an additional data set which allows to converge toward a new synthetic population whose global statistical properties are more satisfying.
Disciplines :
Space science, astronomy & astrophysics
Author, co-author :
Petit, Alexis ; University of Namur, Namur, Belgium
Casanova, Daniel; Centro Universitario de la Defensa, Saragossa, Spain
Dumont, Morgane ; Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Quantitative Models and Methods in Management ; University of Namur, Namur, Belgium
Lemaître, Anne; University of Namur, Namur, Belgium
Language :
English
Title :
Creation of a synthetic population of space debris to reduce discrepancies between simulation and observations
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE] MINECO - Gobierno de Espana. Ministerio de Economia y Competitividad [ES]
Funding text :
Acknowledgements The work of A. Petit is supported by a F.R.I.A Ph.D grant. The work of D. Casanova was supported by the Spanish Ministry of Economy and Competitiveness, Project No. ESP2017–87113– R (AEI/FEDER, UE), and by the Aragon Government and European Social Fund (Group E24_17R). This research used resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” (http://www.ptci.unamur. be) located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS under the convention No. 2.4520.11. The PTCI is a member of the “Consortium des quipements de Calcul Intensif (CCI)” (http:// www.ceci-hpc.be).The work of A. Petit is supported by a F.R.I.A Ph.D grant. The work of D. Casanova was supported by the Spanish Ministry of Economy and Competitiveness, Project No. ESP2017–87113–R (AEI/FEDER, UE), and by the Aragon Government and European Social Fund (Group E24_17R). This research used resources of the “Plateforme Technologique de Calcul Intensif (PTCI)” (http://www.ptci.unamur.be) located at the University of Namur, Belgium, which is supported by the F.R.S.-FNRS under the convention No. 2.4520.11. The PTCI is a member of the “Consortium des quipements de Calcul Intensif (CCI)” (http://www.ceci-hpc.be).
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