Title :
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
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;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location :
Shiyang
DOI :
10.1109/ICCIS.2013.59
