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
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;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2005.851187