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 particle filter (CMA-PF), is proposed in this paper. Search abilities of CMA-ES are utilized within proposed method to perform Prior Regularization, which helps the particle filter to generate particles with higher importance weights. This helps the CMA-PF to operate efficiently and prevents degeneracy and sample impoverishment. According to simulation results, efficiency and applicability of CMA-PF is confirmed.