Robust Filtering by Fictitious Noises

Hanshui Zhang, Dapeng Zhang, Wei Wang, Lihua Xie

Research output: Journal article publicationConference articleAcademic researchpeer-review


In this paper, a new approach is presented for robust filtering of a linear discrete-time signal by applying fictitious noise. Modeling errors, in both the numerator and denominator of the transfer functions, are parameterized by using random variables with zero mean and known covariance. The robust performance is obtained by minimizing the mean square estimation error over all of the random parameter and noise. To derive a robust estimator, the uncertainties in the model are incorporated into two mutually uncorrelated fictitious noises with zero means. The covariances of the fictitious noises are computed by using two formulas that are presented in this paper. An illustrative example shows the effectiveness of our approach.
Original languageEnglish
Pages (from-to)1280-1284
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
Publication statusPublished - 1 Dec 2003
Event42nd IEEE Conference on Decision and Control - Maui, HI, United States
Duration: 9 Dec 200312 Dec 2003


  • Fictitious Noise
  • Filtering
  • Innovation
  • Robust
  • Stochastic
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization


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