• DocumentCode
    882444
  • Title

    A modified Gaussian sum approach to estimation of non-Gaussian signals

  • Author

    Caputi, Mauro J. ; Moose, Richard L.

  • Author_Institution
    Dept. of Eng., Hofstra Univ., Hempstead, NY, USA
  • Volume
    29
  • Issue
    2
  • fYear
    1993
  • fDate
    4/1/1993 12:00:00 AM
  • Firstpage
    446
  • Lastpage
    451
  • Abstract
    A Gaussian sum estimation algorithm has previously been developed to deal with noise processes that are non-Gaussian. Inherent in this algorithm is a serious growing memory problem that causes the number of terms in the Gaussian sum to increase exponentially at each iteration. A modified Gaussian sum estimation algorithm using an adaptive filter is developed that avoids the growing memory problem of the previous algorithm while providing effective state estimation. The adaptive filter is comprised of a fixed set of estimators operating in parallel with each individual estimate possessing its own corresponding weighting term. A simulation example illustrates the new non-Gaussian estimation technique
  • Keywords
    Kalman filters; adaptive filters; digital filters; digital simulation; noise; parallel processing; signal processing; state estimation; Kalman filter; adaptive filter; estimation algorithm; memory; modified Gaussian sum; noise; nonGaussian noise; simulation; state estimation; Adaptive filters; Approximation algorithms; Density functional theory; Density measurement; Gaussian noise; Markov processes; Probability; Random processes; Random variables; Signal processing; State estimation;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/7.210082
  • Filename
    210082