Gaussian filters for nonlinear filtering problems

@article{Ito2000GaussianFF,
  title={Gaussian filters for nonlinear filtering problems},
  author={Kazufumi Ito and Kaiqi Xiong},
  journal={IEEE Trans. Autom. Control.},
  year={2000},
  volume={45},
  pages={910-927}
}
We develop and analyze real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the optimal filter. We also discuss the mixed Gaussian filters in which the conditional probability density is approximated by the sum of Gaussian distributions. A new update rule of weights for Gaussian sum filters is proposed. Our numerical tests… 

Gaussian filter for nonlinear filtering problems

  • K. Ito
  • Computer Science
    Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187)
  • 2000
This work develops and analyzes real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions and develops efficient and accurate numerical integration of the proposed filter.

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  • S. SärkkäJouni Hartikainen
  • Computer Science, Mathematics
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  • 2013
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Kalman Filtering for a Generalized Class of Nonlinear Systems and a New Gaussian Quadrature Technique

The class of nonlinear systems treated in this technical note consists of the discrete time non linear systems that are formed by the interconnection of linear systems through static nonlinearities with few inputs, and a new quadrature scheme suitable for nonlinear Kalman filtering is introduced.
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