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http://hdl.handle.net/20.500.12386/24703
Titolo: | Asteroid orbits with Gaia using random-walk statistical ranging | Autori: | Muinonen, Karri Fedorets, Grigori Pentikäinen, Hanna Pieniluoma, Tuomo Oszkiewicz, Dagmara Granvik, Mikael Virtanen, Jenni Tanga, Paolo Mignard, François Berthier, Jérôme DELL'ORO, Aldo Carry, Benoit Thuillot, William |
Data pubblicazione: | 2016 | Rivista: | PLANETARY AND SPACE SCIENCE | Numero: | 123 | Da pagina:: | 95 | Abstract: | We describe statistical inverse methods for the computation of initial asteroid orbits within the data processing and analysis pipeline of the ESA Gaia space mission. Given small numbers of astrometric observations across short time intervals, we put forward a random-walk ranging method, in which the orbital-element phase space is uniformly sampled, up to a limiting χ<SUP>2</SUP>-value, with the help of the Markov-chain Monte Carlo technique (MCMC). The sample orbits obtain weights from the a posteriori probability density value and the MCMC rejection rate. For the first time, we apply the method to Gaia astrometry of asteroids. The results are nominal in that the method provides realistic estimates for the orbital uncertainties and meets the efficiency requirements for the daily, short-term processing of unknown objects. | URI: | http://hdl.handle.net/20.500.12386/24703 | URL: | https://www.sciencedirect.com/science/article/abs/pii/S0032063315003104 | ISSN: | 0032-0633 | DOI: | 10.1016/j.pss.2015.10.010 | Bibcode ADS: | 2016P&SS..123...95M | Fulltext: | reserved |
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