• DocumentCode
    2775306
  • Title

    Information fusion estimation of noise statistics for multisensor systems

  • Author

    Gao, Yuan ; Wang, Weiling ; Deng, Zili

  • Author_Institution
    Dept. of Autom., Heilongjiang Univ., Harbin, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    1116
  • Lastpage
    1120
  • Abstract
    For multisensor linear discrete time invariant system with unknown noise statistics and correlated noises, by the correlation method, the online local estimators of noise variances, correlated matrices and cross covariances can be obtained by solving the different partial correlated function matrix equations. The information fusion noise statistics estimators are presented by averaging the local estimators of noise statistics. Based on the ergodicity of the sample correlated function, it is proved the local and fused estimators of noise statistics are strong consistent, i.e. they converge to corresponding true values with probability one. They can be applied to design the self tuning information fusion filters. A simulation example of three-sensor system with correlated noises shows the effectiveness of the fused estimation.
  • Keywords
    correlation methods; discrete time systems; estimation theory; linear systems; matrix algebra; sensor fusion; signal denoising; statistics; correlated function, ergodicity; correlated noises; cross-covariances; information fusion estimation; linear discrete time invariant system; multisensor systems; noise statistics; partial correlated function matrix equation; self tuning information fusion; Automation; Autoregressive processes; Information filtering; Kalman filters; Multisensor systems; Parameter estimation; Probability; State estimation; Statistics; Technological innovation; Correlated Method; Estimators of Noise Statistics; Information Fusion Estimation; Strong Consistence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5191542
  • Filename
    5191542