Astrometry in Wide-field Surveys
Andras Pal, Gaspar Bakos
Abstract
We present a robust and fast algorithm for performing astrometry and source cross-identification on two dimensional point lists, such as between a catalogue and an astronomical image, or between two images. The method is based on minimal assumptions: the lists can be rotated, magnified and inverted with respect to each other in an arbitrary way. The algorithm is tailored to work efficiently on wide fields with large number of sources and significant non-linear distortions, as long as the distortions can be approximated with linear transformations locally, over the scale-length of the average distance between the points. The procedure is based on symmetric point matching in a newly defined continuous triangle space that consists of triangles generated by an extended Delaunay triangulation. Our software implementation performed at the 99.995% success rate on ~260,000 frames taken by the HATNet project.
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