• DocumentCode
    567689
  • Title

    Online EM algorithm for joint state and mixture measurement noise estimation

  • Author

    Özkan, Emre ; Fritsche, Carsten ; Gustafsson, Fredrik

  • Author_Institution
    Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
  • fYear
    2012
  • fDate
    9-12 July 2012
  • Firstpage
    1935
  • Lastpage
    1940
  • Abstract
    In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.
  • Keywords
    adaptive signal processing; estimation theory; noise; optimisation; particle filtering (numerical methods); expectation-maximization method; joint state; mixture measurement; multimodal measurement; noise adaptive particle filter; noise estimation; nonlinear state space models; online EM algorithm; particle filtering techniques; unknown noise distribution; Approximation methods; Equations; Hidden Markov models; Maximum likelihood estimation; Noise; Noise measurement; Signal processing algorithms;
  • 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
    6290537