A Novel Particle Filter Based on Propagation and Prediction

Author

Xiangfeng, Bai ; Aihua, Li ; Jialei, Li ; Taiyang, Liu

Author_Institution

502 Fac., Xi´´an Inst. of High Technol., Xi´´an, China

Volume

1

fYear

2011

fDate

6-7 Jan. 2011

Firstpage

202

Lastpage

205

Abstract

The problems existing in standard particle filter include large computation and particle degeneration, and a novel particle filter based on propagation and prediction is proposed to solve the problems. In this method, particles after state transition are propagated according to the distribution of state noise, and then the generated filial particles are used to predict corresponding mother particles referring to measurement, then the latest measurement information is fused into estimation. Therefore, the predicted particles are closer to the true state, and the accuracy of particle filter is improved. The efficiency of the algorithm has been proved by experimental results, and the algorithm occupies great predominance with fewer particles.

Keywords

electromagnetic wave propagation; particle filtering (numerical methods); prediction theory; state estimation; particle degeneration; propagation-prediction particle filter; state noise distribution; Accuracy; Estimation; Filtering algorithms; Noise; Particle filters; Prediction algorithms; importance probability density function; particle degeneration; particle filter; state estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on

Conference_Location

Shangshai

Print_ISBN

978-1-4244-9010-3

Type

conf

DOI

10.1109/ICMTMA.2011.56

Filename

5720757