Title :
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
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;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5648123
