Mixture of uniform probability density functions for non linear state estimation using interval analysis

@article{Gning2010MixtureOU,
  title={Mixture of uniform probability density functions for non linear state estimation using interval analysis},
  author={Amadou Gning and Lyudmila Mihaylova and Fahed Abdallah},
  journal={2010 13th International Conference on Information Fusion},
  year={2010},
  pages={1-8}
}
In this work, a novel approach to nonlinear non-Gaussian state estimation problems is presented based on mixtures of uniform distributions with box supports. This class of filtering methods, introduced in the light of interval analysis framework, is called Box Particle Filter (BPF). It has been shown that weighted boxes, estimating the state variables, can be propagated using interval analysis tools combined with Particle filtering ideas. In this paper, in the light of the widely used Bayesian… CONTINUE READING
Highly Cited
This paper has 45 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 26 extracted citations

Box-particle CPHD filter for multi-target tracking

2015 International Conference on Control, Automation and Information Sciences (ICCAIS) • 2015
View 3 Excerpts
Highly Influenced

Box-particle implementation for cardinality balanced multi-target multi-Bernoulli filter

2013 IEEE China Summit and International Conference on Signal and Information Processing • 2013
View 3 Excerpts
Highly Influenced

Set-membership PHD filter

Proceedings of the 16th International Conference on Information Fusion • 2013
View 3 Excerpts
Highly Influenced

Extended target tracking algorithm based on improved Bernoulli filter

2017 3rd IEEE International Conference on Computer and Communications (ICCC) • 2017
View 2 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 16 references

Nonlinear Bayesian estimation using Gaussian sum approximation

D. L. Alspach, H. W. Sorenson
IEEE Trans. Aut. Contr., 17(4):439–448 • 1972
View 5 Excerpts
Highly Influenced

Applied Interval Analysis

View 4 Excerpts
Highly Influenced

Bonnifait . Constraints propagation techniques on intervals for a guaranteed localization using redundant data

A. Gning, Ph.
Intl . J . of Robotics Research • 2003

A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

M. Arulampalam, S. Maskell, N. Gordon, T. Clapp
IEEE Trans. on Signal Proc., 50(2):174–188 • 2002
View 2 Excerpts

and Eds

A. Doucet, N. Freitas
N. Gordon. Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag • 2001
View 2 Excerpts

Similar Papers

Loading similar papers…