• DocumentCode
    3546713
  • Title

    An improved Particle Swarm Optimization Particle Filtering algorithm

  • Author

    Fengrui Zhang ; Jianshu Cao ; Zhenhui Xu

  • Author_Institution
    Res. Inst. Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    2
  • fYear
    2013
  • fDate
    15-17 Nov. 2013
  • Firstpage
    173
  • Lastpage
    177
  • Abstract
    To solve the problem in Particle Swarm Optimization Particle Filtering algorithm that it can be premature too easy to fall into local minima search results, this paper proposes the Particle Swarm Optimization based Fission Bootstrap Particle Filter algorithm. The algorithm first search the space for the particle set by Particle Swarm Optimization, it makes the particle set move to a higher likelihood region, then uses fission bootstrap process to improve the diversity of the particle set, that avoids Particle Degradation caused by premature of the Particle Swarm Optimization. In Monte Carlo simulation of tracking moving target, the tracking performance of Particle Swarm Optimization based Fission Bootstrap Particle Filter algorithm is better than Particle Filtering algorithm in root mean square error(RMSE), also better than that of Particle Swarm Optimization Particle Filtering algorithm.
  • Keywords
    Monte Carlo methods; mean square error methods; particle filtering (numerical methods); particle swarm optimisation; target tracking; Monte Carlo simulation; fission bootstrap particle filter algorithm; local minima search; moving target tracking; particle degradation; particle swarm optimization particle filtering algorithm; root mean square error; Equations; Filtering algorithms; Mathematical model; Particle filters; Particle swarm optimization; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems (ICCCAS), 2013 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-3050-0
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2013.6765312
  • Filename
    6765312