Covariance Matrix Adaptation Particle Filter

Author

Heris, S. Mostapha Kalami ; Khaloozadeh, Hamid

Author_Institution

Control Eng. Dept., K.N. Toosi Univ. of Technol., Tehran, Iran

fYear

2014

fDate

4-6 Feb. 2014

Firstpage

1

Lastpage

6

Abstract

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.

Keywords

covariance matrices; evolutionary computation; nonlinear filters; particle filtering (numerical methods); search problems; CMA-ES; CMA-PF; covariance matrix adaptation evolution strategy; covariance matrix adaptation particle filter; degeneracy prevention; intelligent particle filter; particle generation; particle weight; prior regularization; search abilities; Covariance matrices; Human immunodeficiency virus; Mathematical model; Particle filters; Probability density function; State estimation; CMA-ES; Evolutionary Filtering; Intelligent Filtering; Nonlinear Filtering; Particle Filter; State Estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (ICIS), 2014 Iranian Conference on

Conference_Location

Bam

Print_ISBN

978-1-4799-3350-1

Type

conf

DOI

10.1109/IranianCIS.2014.6802575

Filename

6802575