Hummingbirds optimization algorithm-based particle filter for maneuvering target tracking

  • Zhuoran Zhang
  • Changqiang Huang
  • Dali Ding
  • Shangqin Tang
  • Bo Han
  • Hanqiao HuangEmail author
Original Paper


As a commonly used filtering method for nonlinear non-Gaussian systems, particle filters (PFs) have been successfully applied in the field of maneuvering target tracking. However, particle impoverishment is a major obstacle to the PF performance. To overcome this defect, this paper combines the hummingbirds optimization algorithm (HOA) with a standard PF and proposes an HOA-based PF (HOA-PF) for maneuvering target tracking. The proposed filter treats the particles as individual hummingbirds, simulates the honey-collecting process of hummingbirds in nature and moves the particles as a whole to the high-likelihood region by performing self-searching and guided-searching phases. Moreover, to enhance the particle diversity, the mutation method of the following birds in the HOA is improved. Thus, the distribution of particles in the HOA-PF is reasonable. The results of experiments on the univariate nonstationary growth model and the maneuvering target tracking problem demonstrate the effectiveness of the proposed method.


Particle filter Particle impoverishment Hummingbirds optimization algorithm Maneuvering target tracking 



This work is supported by the National Natural Science Foundation of China under Grant No. 61601505.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest to disclose.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Zhuoran Zhang
    • 1
  • Changqiang Huang
    • 1
  • Dali Ding
    • 1
  • Shangqin Tang
    • 1
  • Bo Han
    • 1
  • Hanqiao Huang
    • 2
    Email author
  1. 1.Aeronautics Engineering CollegeAir Force Engineering UniversityXi’anChina
  2. 2.Unmanned System Research InstituteNorthwestern Polytechnical UniversityXi’anChina

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