TITLE:
Particle Filtering with Multi Proposal Distributions
AUTHORS:
Fasheng WANG, Qingjie ZHAO, Yingbo ZHANG, Liqun ZHANG
KEYWORDS:
Sequential Monte Carlo, Proposal Distribution, Multiple Proposal Distributions
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.1 No.1,
June
6,
2008
ABSTRACT: Particle filtering algorithm has been applied to various fields due to its capacity to handle nonlinear/non-Gaussian dynamic problems. One crucial issue in particle filtering is the selection of the proposal distribution that generates the particles. In this paper, we give a novel strategy for selecting proposal distribution. Firstly, divide-conquer strategy is used, in which the particles used are divided into several parts. Afterward, different parts of particles are drawn from different proposal distributions. People can flexibly adjust how many of the particles drawn from specific proposal distributions according to their idiographic requirements. We provide simulation results that show its efficiency and performance.