We propose to approximate the PHD

by a set of weighted random samples which are propagated

over time using a generalised SMC method. The

resulting algorithm is very attractive as it is general

enough to handle non-linear non-Gaussian dynamics

and the computational complexity is independent of the

(time-varying) number of targets.