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 CMAPF to operate efficiently and prevents degeneracy and sample impoverishment. According to simulation results, efficiency and applicability of CMA-PF is confirmed.