• DocumentCode
    567490
  • Title

    Gaussian mixture PHD and CPHD filtering with partially uniform target birth

  • Author

    Beard, Michael ; Vo, Ba-Tuong ; Vo, Ba-Ngu ; Arulampalam, Sanjeev

  • Author_Institution
    Maritime Oper. Div., DSTO Australia, Rockingham, WA, Australia
  • fYear
    2012
  • fDate
    9-12 July 2012
  • Firstpage
    535
  • Lastpage
    541
  • Abstract
    The standard Gaussian Mixture Probability Hypothesis Density (GMPHD) filter and Cardinalised Probability Hypothesis Density (GMCPHD) filter require the target birth model to take the form of a Gaussian mixture. Although any density (including a uniform density), can be approximated using a sum of Gaussians, this can be inefficient in practice, especially when a large number of Gaussians is required to achieve the desired accuracy. A better alternative in the case of an uninformative birth model would be to directly use a uniform density instead of a Gaussian mixture approximation. In this paper we present new forms of the GMPHD and GMCPHD filtering equations, which allow part of the target birth model to take on a uniform distribution, thus obviating the need to use large Gaussian mixtures to approximate a uniform birth density.
  • Keywords
    Gaussian distribution; filtering theory; probability; CPHD filtering equation; Gaussian mixture PHD filter; Gaussian mixture approximation; cardinalised probability hypothesis density filter; partially uniform target birth model; standard Gaussian mixture probability hypothesis density filter; Approximation methods; Clutter; Computational modeling; Density measurement; Equations; Mathematical model; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion (FUSION), 2012 15th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4673-0417-7
  • Electronic_ISBN
    978-0-9824438-4-2
  • Type

    conf

  • Filename
    6289848