Mathematics – Probability
Scientific paper
Jan 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006adspr..38.2107s&link_type=abstract
Advances in Space Research, Volume 38, Issue 9, p. 2107-2116.
Mathematics
Probability
Scientific paper
Algorithms for the derivation of appropriate collision avoidance strategies are presented in this paper together with results for commonly used operational orbits. It will be demonstrated that collision avoidance strategies for an accepted collision probability level are characterized by the number of evasive manoeuvres, the expected risk reduction, the false alarm rate, and the required ΔV and propellant mass fraction. The assessment of avoidance strategies takes into account statistical models of the observable space object environment, as provided by ESA’s MASTER-2001 model, and a mathematical framework for the collision risk estimation as used in satellite operations. The MASTER-2001 model is used to mimic the trackable space object population larger than 10 cm in diameter. A size-dependent correction is applied to simulate the corresponding catalogue of United States Strategic Command (USSTRATCOM), which is incomplete at small sizes. The adopted, ‘observable’ object population is then grouped by orbit types to enable group-wise associations with derived catalogue orbit determination uncertainties. The relevance of these uncertainties (error co-variances) in the derivation of avoidance strategies is highlighted. Sample results for some operational space missions are presented, assessing the most appropriate collision avoidance strategies for different types of target orbits. The results were obtained with the Assessment of Risk Event Statistics (ARES) software package, which is part of ESA’s Debris Risk Assessment and Mitigation Analysis software (DRAMA). DRAMA is intended to verify compliance of ESA space programs with a European Code of Conduct for Space Debris Mitigation. It has been developed by a European team under ESA contract; the ARES tool has been developed by DEIMOS Space S.L.
Belló-Mora Miguel
Klinkrad Heiner
Sánchez-Ortiz Noelia
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