A biological inspired improvement strategy for Particle Filters

Abstract

Particle Filters (PF) is a model estimation technique based on simulation. But two problems, namely particle impoverishment and sample size dependency, frequently occur during the particle updating stage and these problems will reduce the accuracy of the estimation results. In order to avoid these problems, Ant Colony Optimization is incorporated into the generic particle filter before the updating stage. After the optimization, particle samples will move closer to their local highest posterior density function and better estimation results can be produced.