  We describe a Bayesian sampling model for linking and constraining orbit
models from angular observations of "streaks" in optical telescope images. Our
algorithm is particularly suited to situations where the observation times are
small fractions of the orbital periods of the observed objects or when there is
significant confusion of objects in the observation field. We use Markov Chain
Monte Carlo to sample from the joint posterior distribution of the parameters
of multiple orbit models (up to the number of observed tracks) and parameters
describing which tracks are linked with which orbit models. Using this
algorithm, we forecast the constraints on geosynchronous (GEO) debris orbits
achievable with the planned Large Synoptic Survey Telescope (LSST). Because of
the short 15 second exposure times, preliminary orbit determinations of GEO
objects from LSST will have large and degenerate errors on the orbital
elements. Combined with the expected crowded fields of GEO debris it will be
challenging to reliably link orbital tracks in LSST observations given the
currently planned observing cadence.
