• DocumentCode
    3519397
  • Title

    A Novel Particle Filter for Nonlinear Non-Gaussian Estimation

  • Author

    Lu, Chuanguo ; Feng, Xinxi ; Lei, Yu ; Kong, Yunbo ; Zhang, Di

  • Author_Institution
    Dept. of Command Autom. Eng., Air Force Eng. Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    28-29 May 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A novel improved particle filter, cubature particle filter, is proposed for the estimation of nonlinear non-Gaussian system. Each particle is estimated by means of cubature kalman filter. The importance density function gets closer to the real posterior after taking the current observation into consideration on the basis of state transition. Both theoretical analysis and simulation experiment show that the cubature particle filter performs much better than the other parallel filters.
  • Keywords
    Gaussian processes; particle filtering (numerical methods); cubature particle filter; density function; nonlinear Non-Gaussian estimation; Accuracy; Atmospheric measurements; Current measurement; Kalman filters; Particle filters; Particle measurements; Proposals;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9855-0
  • Electronic_ISBN
    978-1-4244-9857-4
  • Type

    conf

  • DOI
    10.1109/ISA.2011.5873275
  • Filename
    5873275
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3519397