The astrometric Gaia-FUN-SSO observation campaign of 99 942 Apophis
W. Thuillot, D. Bancelin, A. Ivantsov, J. Desmars, M. Assafin, S., Eggl, D. Hestroffer, P. Rocher, B. Carry, P. David, L. Abe, M. Andreev, J.-E., Arlot, A. Asami, V. Ayvasian, A. Baransky, M. Belcheva, Ph. Bendjoya, I., Bikmaev, O. A. Burkhonov, U. Camci, A. Carbognani, F. Colas

TL;DR
This paper reports on a comprehensive astrometric observation campaign of asteroid Apophis using Gaia-FUN-SSO, demonstrating improved data quality and potential for better orbit prediction during its 2029 close approach.
Contribution
It introduces a new reduction process using UCAC4 that enhances astrometric accuracy and provides a large set of unpublished data for asteroid orbit refinement.
Findings
Improved astrometric precision with UCAC4 catalog
Unpublished 2103 astrometric positions released
Enhanced orbit uncertainty reduction for Apophis
Abstract
Astrometric observations performed by the Gaia Follow-Up Network for Solar System Objects (Gaia-FUN-SSO) play a key role in ensuring that moving objects first detected by ESA's Gaia mission remain recoverable after their discovery. An observation campaign on the potentially hazardous asteroid (99 942) Apophis was conducted during the asteroid's latest period of visibility, from 12/21/2012 to 5/2/2013, to test the coordination and evaluate the overall performance of the Gaia-FUN-SSO . The 2732 high quality astrometric observations acquired during the Gaia-FUN-SSO campaign were reduced with the Platform for Reduction of Astronomical Images Automatically (PRAIA), using the USNO CCD Astrograph Catalogue 4 (UCAC4) as a reference. The astrometric reduction process and the precision of the newly obtained measurements are discussed. We compare the residuals of astrometric observations that we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
