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Given a set of astrometric observations of the same object, the problem oforbit determination is to compute the orbit and to assess its uncertainty andreliability. For the next generation surveys, with much larger number densityof observed objects, new algorithms or substantial revisions of the classicalones are needed. The problem has three main steps, preliminary orbit, leastsquares orbit, and quality control. The classical theory of preliminary orbitswas incomplete: the consequences of the topocentric correction had not beenfully studied. We show that it is possible to account for this correction,possibly with an increase in the number of preliminary solutions, withoutimpairing the overall orbit determination performance. We have developedmodified least squares orbit determination algorithms that can be used toimprove the reliability of the procedure. We have tested the complete procedureon two simulations with number densities comparable to that expected from thenext generation surveys such as Pan-STARRS and LSST. To control the problem offalse identifications we have introduced a quality control on the fit residualsbased on an array of metrics and a procedure to remove duplications andcontradictions in the output. The results confirm that large sets ofdiscoveries can be obtained with good quality orbits and very high success ratelosing only 0.6 to 1.3% of objects and a false identification rate in the range0.02 to 0.06%.

Orbit Determination with Topocentric Correction: Algorithms for the Next Generation Surveys