@inproceedings{4f6d06220a644e90bf9a464e9fa94f4d,
title = "Gaussian sum filter for state estimation of Markov jump nonlinear system",
abstract = "This paper proposes the Gaussian sum filtering (GSF) framework for the state estimation of Markov jump nonlinear systems (MJNLSs). Through presenting the Gaussian sum approximations about the model-conditioned state posterior probability density function (PDF) and the model-conditioned measurement posterior predictive PDF, a general GSF framework in the minimum mean square error (MMSE) sense is derived. The Minor Gaussian-set design is utilized to merge the Gaussian components at the beginning, which can effectively limit the computational requirements. Simulation results demonstrate that the proposed method performs almost as well as the interacting multiple model particle filter (IMM-PF) but with much lower computational cost.",
keywords = "Gaussian sum approximation, Markov jump nonlinear systems, Moment matching, Polynomial interpolation",
author = "Li Wang and Yan Liang and Xiaoxu Wang and Linfeng Xu",
note = "Publisher Copyright: {\textcopyright} 2014 International Society of Information Fusion.; 17th International Conference on Information Fusion, FUSION 2014 ; Conference date: 07-07-2014 Through 10-07-2014",
year = "2014",
month = oct,
day = "3",
language = "英语",
series = "FUSION 2014 - 17th International Conference on Information Fusion",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "FUSION 2014 - 17th International Conference on Information Fusion",
}