Modified unscented particle filter for nonlinear Bayesian tracking

A modified unscented particle filtering scheme for nonlinear tracking is proposed, in view of the potential drawbacks (such as, particle impoverishment and numerical sensitivity in calculating the prior) of the conventional unscented particle filter (UPF) confronted in practice. Specifically, a different derivation of the importance weight is presented in detail. The proposed method can avoid the calculation of the prior and reduce the effects of the impoverishment problem caused by sampling from the proposal distribution. Simulations have been performed using two illustrative examples and results have been provided to demonstrate the validity of the modified UPF as well as its improved performance over the conventional one.