Ant Colony Estimator: An intelligent particle filter based on

Based on Ant Colony Optimization for Continuous Domains ( ACO R ) and Particle Filter (PF), an intelligent particle filter, namely Ant Colony Estimator (ACE), is proposed in this paper. Modeling and search abilities of ACO R are incorporated into the standard particle filtering framework to improve the estimation performance and overcome the well-known problems of Degeneracy and Sample Impoverishment. ACO R operators implicitly use measurement and previous particle information, to generate probably better particles. Simulation results are given for two examples and ACE is compared to other types of particle filters. The obtained results confirm the efficiency and applicability of ACE.