New version of a MCMC data association algorithm for non-linear observation model - application to the tracking problem with French OTH radar Nostradamus

Over-The-Horizon(OTH) Radars provide a survey of wide areas, using ionospheric reflections of the electromagnetic waves. Most of the time they have to face multipath problems: state estimation has to be done with measurements involving different observation models. To tackle this measurement-to-observation-model association problem, the Monte Carlo Data Association (MCDA) algorithm, and a derivative one, the Iterated Conditional Mode Data Association (ICMDA) have been developed. They only applied in linear context. We propose new versions of these algorithms well adapted to non-linear problems. Our two algorithms are applied, through numerical simulations, to a concrete case: target tracking with the French OTH radar Nostradamus, in clutter environment.