A novel proposal distribution for particle filter

Author

Ju, Bing ; Zhang, Zenghui ; Zhu, Jubo

Author_Institution

Coll. of Sci., Nat. Univ. of Defense Technol., Changsha, China

Volume

7

fYear

2010

fDate

16-18 Oct. 2010

Firstpage

3120

Lastpage

3124

Abstract

In order to solve the problem of degeneracy in particle filtering algorithm, a novel proposal distribution is designed in this paper. The principal idea of the proposal distribution is to fuse the latest observations together with the previous filtering estimate and the prior model information. In that case, the one-step smoothing estimate of the state is employed. Simulation results show that the improved particle filtering algorithm based on this proposal distribution is more accuracy than that of standard particle filter, the extended Kalman particle filter and the unscented particle filter. Besides, the particles drawn from the distribution proposed is more efficient.

Keywords

Kalman filters; particle filtering (numerical methods); degeneracy; extended Kalman particle filter; particle filtering algorithm; proposal distribution; unscented particle filter; Approximation algorithms; Filtering algorithms; Monte Carlo methods; Particle filters; Proposals; Smoothing methods; one-step state smoothing; particle filter; proposal distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2010 3rd International Congress on

Conference_Location

Yantai

Print_ISBN

978-1-4244-6513-2

Type

conf

DOI

10.1109/CISP.2010.5648123

Filename

5648123