A Novel Auxiliary Variable Particle Filter

Auxiliary variable particle filter (AVPF) at smaller process noise, state estimation can not get better filtering accuracy, this paper presents a novel auxiliary variable particle filter. Regularization will be introduced into resampling of auxiliary variable particle filter, In the resampling, the discrete probability distribution function approximated by a continuous distribution function, which not only retains the feature that AVPF based on the size of likelihood values revises the original particles are concentrated weights before resampling, from smooth posterior density resampling, after the introduction of regularization also able to maintain the diversity of particle in the resampling, increasing the number of the effective particles, can effectively inhibit the degradation of the sample. For doublet, a highly nonlinear system model has been widely used, in the process of selecting a different noise, carry out Monte Carlo simulations. Simulation results show that the novel variable particle filter has better filtering accuracy.