An unscented particle filter for GMTI tracking

Abstract

Ground moving target indicator (GMTI) tracking is often carried out using extended Kalman filters, as in the variable-structure interacting multiple-model (VS-IMM) filter. In some scenarios, however, this is considered to be inadequate. It has been shown that in this case, a particle filter can give better performance. Such a filter, the variable-structure multiple-model particle filter (VS-MMPF), is given in the literature. In this paper we present a new approach to solving the GMTI tracking problem using a particle filter. We have developed an unscented particle filter, where the particles model the uncertainty over the motion model while, conditional upon the model, the target state is modelled using an unscented Kalman filter. Simulation results show that the UPF-based filter gives performance similar to the VS-MMPF with significantly fewer particles and better results than the standard VS-IMM approach.