The asteroid identification problem IV: Attributions

Existing archives of asteroid observations contain many objects with very s hort observed arcs, In this paper we present a method that we have used wit h considerable success to attribute these short are "discoveries" to other objects with better defined orbits. The method consists of a three-stage fi ltering process whereby several billion possible attribution/orbit pairs ar e systematically analyzed with more and more exact algorithms, at each stag e rejecting improbable cases. The first stage compares an attributable, by definition a synthetic observation representative of all the observations o ver a short are, with the predicted observation for each available orbit. T he second stage compares the proposed attributable observations with predic ted positions from the known orbit using conventional linear covariance tec hniques, considering both the position and motion on the celestial sphere. In the final filter we attempt to compute a best-fitting orbit by different ial corrections using the combined dataset, With this algorithm we have fou nd 1675 attributions in approximately one year of operations, in addition t o 902 identifications found with another algorithm. We discuss the lessons learned from this one-year experiment and the possibilities of further impr ovement and automation of the procedure. (C) 2001 Academic Press.