Title :
A Novel Particle Filter for Nonlinear Non-Gaussian Estimation
Author :
Lu, Chuanguo ; Feng, Xinxi ; Lei, Yu ; Kong, Yunbo ; Zhang, Di
Author_Institution :
Dept. of Command Autom. Eng., Air Force Eng. Univ., Xi´´an, China
Abstract :
A novel improved particle filter, cubature particle filter, is proposed for the estimation of nonlinear non-Gaussian system. Each particle is estimated by means of cubature kalman filter. The importance density function gets closer to the real posterior after taking the current observation into consideration on the basis of state transition. Both theoretical analysis and simulation experiment show that the cubature particle filter performs much better than the other parallel filters.
Keywords :
Gaussian processes; particle filtering (numerical methods); cubature particle filter; density function; nonlinear Non-Gaussian estimation; Accuracy; Atmospheric measurements; Current measurement; Kalman filters; Particle filters; Particle measurements; Proposals;
Conference_Titel :
Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9855-0
Electronic_ISBN :
978-1-4244-9857-4
DOI :
10.1109/ISA.2011.5873275
