Particle estimation algorithm using correlation of observation for nonlinear system state

摘要

A particle estimation algorithm, where the weight of the particle is proportional to the correlation coefficient of observations, is presented. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than SIR, APF, RPF, and GPF.