  The problem of simultaneous trajectography of several dynamical objects is
formulated as an optimization problem. The available observations consist in a
series of photographs showing undiscriminated objects. The goal is to find the
object initial states so that the resulting trajectories match as well as
possible the set of observations. An assignment problem is solved at each
observation date by the Hungarian method, yielding a deviation cost between the
simulated trajectories and the measurements. A fitness function summing the
deviation costs is minimized by a particle swarm algorithm. The method is
illustrated on a space orbitography application.
