• DocumentCode
    1808054
  • Title

    Multi-Bernoulli filter for superpositional sensors

  • Author

    Nannuru, Santosh ; Coates, Mark

  • Author_Institution
    Electr. & Comput. Eng. Dept., McGill Univ., Montreal, QC, Canada
  • fYear
    2013
  • fDate
    9-12 July 2013
  • Firstpage
    1632
  • Lastpage
    1637
  • Abstract
    The superpositional sensor model encompasses an important class of sensors such as acoustic sensors and radio-frequency sensors used for multi-target tracking. Recently, random finite set based moment filters such as PHD and CPHD filters have been developed for superpositional sensors. In this paper we derive multi-Bernoulli filter equations for superpositional sensors. The multi-Bernoulli update is derived by defining a conditional PHD for each component of the multi-Bernoulli random finite set and then following an approach similar to that used in deriving the CPHD filter update equation for superpositional sensors. The cardinality distribution is also updated along with the conditional PHD.
  • Keywords
    filtering theory; sensors; CPHD filters; acoustic sensors; cardinality distribution; conditional PHD; multiBernoulli filter equations; multiBernoulli random finite set; multitarget tracking; radiofrequency sensors; random finite set based moment filters; superpositional sensor model; Covariance matrices; Equations; Mathematical model; Sensor fusion; Target tracking; CPHD filter; PHD filter; multi-Bernoulli filter; multi-target tracking; random finite set; superpositional sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion (FUSION), 2013 16th International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-605-86311-1-3
  • Type

    conf

  • Filename
    6641196