Particle Filter Based on Pseudo Parallel Genetic Algorithm

Author

Li Ziyu ; Liu Yan ; Song Lei ; Cheng Ying

Author_Institution

Beijing Aerosp. Control Center, Beijing, China

fYear

2013

fDate

21-23 June 2013

Firstpage

195

Lastpage

198

Abstract

In order to inhibit the degeneracy phenomenon in particle filter (PF) and the sample impoverishment caused by resampling, this paper proposes particle filter technology based on pseudo parallel genetic algorithm (PPGA-PF), in which PPGA improves PF. Theoretical analysis and computer simulation on PPGA-PF, PF and EKF in the Global Positioning System (GPS) show that filtering performance of the proposed technology has made apparent improvement.

Keywords

Global Positioning System; Kalman filters; genetic algorithms; nonlinear filters; parallel algorithms; particle filtering (numerical methods); sampling methods; EKF; GPS; Global Positioning System; PPGA-PF; degeneracy phenomenon; extended Kalman filter; particle filter technology; pseudo parallel genetic algorithm; resampling; sample impoverishment; Convergence; Filtering algorithms; Genetic algorithms; Global Positioning System; Monte Carlo methods; Particle filters; Global Positioning System; Non-linear filter; degeneracy phenomenon; particle filter; pseudo parallel genetic algorithm; sample impoverishment;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.59

Filename

6642974