DocumentCode
1003498
Title
Comments on "Gaussian particle filtering"
Author
Wu, Yuanxin ; Xiaoping Hu ; Hu, Xiaoping ; Meiping Wu
Author_Institution
Dept. of Autom. Control, Nat. Univ. of Defense Technol., Hunan, China
Volume
53
Issue
8
fYear
2005
Firstpage
3350
Lastpage
3351
Abstract
With the Gaussian assumption, the above paper proposed an optimal Gaussian filer under the particle filtering framework. This comment presents a different perspective from the standpoint of the conventional Gaussian filters. In this respect, the Gaussian particle filter actually extends the conventional Gaussian filter using Monte Carlo integration and the Bayesian update rule. Hopefully, the use of quasi-Monte Carlo integration in place of Monte Carlo integration will improve the particle filtering.
Keywords
Bayes methods; Gaussian distribution; filtering theory; integration; Bayesian update rule; Gaussian particle filtering; optimal Gaussian filter; quasi-Monte Carlo integration; Bayesian methods; Filtering; Gaussian distribution; Gaussian processes; Kalman filters; Monte Carlo methods; Multidimensional systems; Particle filters; Probability density function; State estimation; Bayesian solution; Gaussian filter; Kalman; Monte Carlo integration; particle filtering; quasi-Monte Carlo integration;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2005.851187
Filename
1468528
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