Covariance Matrix Adaptation Particle Filter

Based on Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Particle Filter (PF), an intelligent particle filter, namely Covariance Matrix Adaptation ParticleFilter (CMA-PF), is proposed in this paper. Search abilities of CMA-ES are utilized within proposed method to perform PriorRegularization, which helps the particle filter to generate particles with higher importance weights. This helps the CMAPF to operate efficiently and prevents degeneracy and sampleimpoverishment. According to simulation results, efficiency and applicability of CMA-PF is confirmed.

کلیدواژه ها:

Particle Filter ، CMA-ES ، Intelligent Filtering ، Evolutionary Filtering ، Nonlinear Filtering ، State Estimation