Abstract
This paper illustrates a novel taxonomy method for LEO space debris population whose aim is to classify the LEO space debris objects such that it is possible to identify, safety wise, for each one the most suitable Active Debris Removal (ADR) capture method. The method is formulated in two distinct layers. In the first layer, a main class of an object is identified, based on its most prominent dynamical and physical traits. At this stage identifying the most suited ADR method is still a difficult task, due to the crude nature of the parameters used for the classification. The second taxonomic layer is thus performed on top of the first one. In it the break-up risk index and levels of non-cooperativeness of an object are identified and the ADR association is refined. Examples of application of the developed taxonomy are presented at the end of the paper and conclusions are drawn regarding the best methods to be used for the main categories of LEO space debris under investigation for future ADR missions.
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Acknowledgements
The research work here presented was supported by the Marie Curie Initial Training Network Stardust, FP7-PEOPLE-2012-ITN, Grant Agreement 317185. Thus, the authors would like to thank the European Commission and the Research Executive Agency for their support and funding.
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Jankovic, M., Kirchner, F. (2018). Taxonomy of LEO Space Debris Population for ADR Capture Methods Selection. In: Vasile, M., Minisci, E., Summerer, L., McGinty, P. (eds) Stardust Final Conference. Astrophysics and Space Science Proceedings, vol 52. Springer, Cham. https://doi.org/10.1007/978-3-319-69956-1_8
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DOI: https://doi.org/10.1007/978-3-319-69956-1_8
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