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Particle filter with importance density function generated by updated system equation

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Abstract

The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function (IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters (PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.

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Authors and Affiliations

  1. School of Aeronautics, Northwestern Polytechnical University, Xi’an, 710072, China

    Jun-yi Zuo  (左军毅) & Wei Zhang  (张炜)

  2. 106 Institute, Qing’an Group Corporation Limited, Xi’an, 710077, China

    Ying-na Jia  (贾颖娜)

  3. State Key Laboratory of Integrated Service Networks (Xidian University), Xi’an, 710071, China

    Quan-xue Gao  (高全学)

Authors
  1. Jun-yi Zuo  (左军毅)
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  2. Ying-na Jia  (贾颖娜)
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  3. Wei Zhang  (张炜)
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  4. Quan-xue Gao  (高全学)
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Corresponding author

Correspondence to Jun-yi Zuo  (左军毅).

Additional information

Foundation item: Project(61271296) supported by the National Natural Science Foundation of China

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Zuo, Jy., Jia, Yn., Zhang, W. et al. Particle filter with importance density function generated by updated system equation. J. Cent. South Univ. 20, 2700–2707 (2013). https://doi.org/10.1007/s11771-013-1786-2

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  • DOI: https://doi.org/10.1007/s11771-013-1786-2

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