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Paper: Robust Registration of Astronomy Catalogs
Volume: 523, Astronomical Data Analysis Software and Systems XXVIII
Page: 583
Authors: Tian, F.; Budavári, T.; Basu, A.
Abstract: Due to a small number of reference sources, the astrometric calibration of images with a small field of view is often inferior to the internal accuracy of sources detected in the images. One important experiment with such challenges is the Hubble Space Telescope (HST). A possible solution is to cross-calibrate overlapping fields instead of just relying on standard stars. Following Budavári & Lubow (2012), we use infinitesimal 3D rotations for fine-tuning the calibration but re-formalize the objective to be robust to a large number of false candidates in the initial set of associations. Using Bayesian statistics, we accommodate bad data by explicitly modeling the quality which yields a formalism essentially identical to M-estimation in robust statistics. Our preliminary results on simulated catalogs show great potentials for improving the HST calibration.
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