A New Mixed Particle Filter Based on an Auxiliary Model

Abstract

Particle filter is an effective method for non-linear filter and it has been gained special attention of researchers in various fields. There will be a new mixed particle filter (PUPF) proposed in this paper based on the general particle filter and the unscented particle filter. lt first uses the general particle filter to generate particles for estimating the state at time k and then a new auxiliary model will be introduced. We would use the unscented particle filter to estimate the state at time k the second time. This structure makes use of the latest observation information, it has small error and better stability. The experimental results indicate that the proposed particle filter's performance outperforms the other four particle filters .The result indicates that the PUPF is a useful method for nonlinear filter problems.