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New methods for space debris collision assessment

Published online by Cambridge University Press:  05 January 2015

Daniel Casanova
Affiliation:
University of Namur, naXys - Department of Mathematics, 8 Rempart de la Vierge, 5000, Namur, Belgium email: daniel.casanova@unamur.be
Chiara Tardioli
Affiliation:
University of Strathclyde, Department of Mechanical & Aerospace Engineering, 75 Montrose Street, Glasgow, UK
Anne Lemaître
Affiliation:
University of Namur, naXys - Department of Mathematics, 8 Rempart de la Vierge, 5000, Namur, Belgium email: daniel.casanova@unamur.be
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Abstract

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Collisions between two pieces of space debris or between a piece of debris and an operative satellite is a real problem. Furthermore, collisions are responsible for the creation of new space debris systematically. The way to exclude the possibility of a collision consists of analysing the trajectories and looking for a time of coincidence. However, the analysis of all pairs of objects collected in a large orbit catalogue is unfeasible. The proposed method consists of reducing the possible pairs of candidates for a collision into a short list of pairs at real risk of collision. The method is based on a three-filter sequence: the first two filters are based on the geometry of the orbits, while the third one searches for a time of coincidence. This new method is tested resulting into an efficient tool for space debris collision assessment.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2014 

References

Casanova, D., Tardioli, C., & Lemaitre, A. 2014, MNRAS, 442 (4), 32353242Google Scholar
Casanova, D. & Lemaitre, A. 2014, Submitted to Celest. Mech. Dyn. Astr.Google Scholar
Delsate, N., Lemaitre, A., Carletti, T., & Robutel, P. 2010, Celest. Mech. Dyn. Astr., 108 (3), 275300Google Scholar
Dimare, L., Farnocchia, D., Gronchi, G. F., Milani, A., Bernardi, F., & Rossi, A. 2011, Advanced Maui Optical and Space Surveillance Technologies Conference, 1, 51Google Scholar
Gronchi, G. F. 2002, SIAM J. Sci. Comput., 24 (1), 6180CrossRefGoogle Scholar
Gronchi, G. & Tommei, G. 2007, Discret. Contin. Dyn-B., 7 (4), 755778Google Scholar
Gronchi, G. F., Dimare, L., & Milani, A. 2010, Celest. Mech. Dyn. Astr., 107 (3), 299318Google Scholar
Hoots, F. R. & Crawford, L. L., Roehrich, R. L. 1984, Celest. Mech., 33 (2), 143158Google Scholar
Hubaux, C., Lemaitre, A., Delsate, N., & Carletti, T. 2012, Adv. Sp. Res., 49 (10), 14721486CrossRefGoogle Scholar
Lemaitre, A., Delsate, N., & Valk, S. 2009, Celest. Mech. Dyn. Astr., 104 (4), 383402Google Scholar
Milani, A., Tommei, G., Chesley, S., Sansaturio, M., & Valsecchi, G. 2005, Icarus, 173 (2), 362384Google Scholar
Pardini, C. & Anselmo, L. 2011, Adv. Sp. Res., 48 (3), 557569Google Scholar
Valk, S., Lemaitre, A., & Anselmo, L. 2008, Adv. Sp. Res., 41 (7), 10771090Google Scholar
Valk, S., Lemaitre, A., & Deleflie, F. 2009, Adv. Sp. Res., 43 (7), 10701082Google Scholar
Valk, S., Delsate, N., Lemaitre, A., & Carletti, T. 2009, Adv. Sp. Res., 43 (10), 15091526CrossRefGoogle Scholar