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Firefly Algorithm-Based Particle Filter for Nonlinear Systems

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Abstract

A particle filter (PF) has been considered one of the most useful tools for nonlinear non-Gaussian systems. However, the estimation accuracy is limited by sample impoverishment due to resampling. Therefore, a firefly algorithm-based PF is proposed to solve this problem. In the proposed algorithm, the resampling step is performed based on the firefly algorithm. Finally, simulations are conducted to illustrate the superior performance of the proposed algorithm over that of a PF and a regularized particle filter.

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Acknowledgements

Funding was provided by National Natural Science Foundation of China (Grant No. 61573113).

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Authors and Affiliations

  1. College of Automation, Harbin Engineering University, Harbin, 150001, China

    Weidong Zhou, Lu Liu & Jiaxin Hou

Authors
  1. Weidong Zhou
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  2. Lu Liu
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  3. Jiaxin Hou
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Correspondence to Lu Liu.

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Zhou, W., Liu, L. & Hou, J. Firefly Algorithm-Based Particle Filter for Nonlinear Systems. Circuits Syst Signal Process 38, 1583–1595 (2019). https://doi.org/10.1007/s00034-018-0927-0

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  • DOI: https://doi.org/10.1007/s00034-018-0927-0

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