Minimum Weighted Frobenius Norm Discrete-Time FIR Filter with Embedded Unbiasedness

Sung Hyun You, Choon Ki Ahn, Yuriy S. Shmaliy, Shunyi Zhao

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, we propose a new receding horizon finite impulse response (FIR) filter that minimizes the weighted Frobenius norm with embedded unbiasedness in discrete-time state-space. The filter, called the discrete-time weighted Frobenius norm unbiased FIR (DTWFNUF) filter, belongs to a class of maximum likelihood estimators. The Frobenius norm is introduced and minimized as a performance criterion to the filter gain matrix. It is shown that the DTWFNUF filter design problem can be cast into the optimization problem with the equality constraint and the filter gain matrix obtained by the Lagrange multiplier method. Higher robustness of the proposed filter is demonstrated in a comparison with the Kalman filter (KF) and minimum variance unbiased (MVU) FIR (MVUFIR) filter based on a numerical example of the F-404 gas turbine engine.

Original languageEnglish
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
DOIs
Publication statusAccepted/In press - 2018 Feb 28

Fingerprint

FIR filters
Lagrange multipliers
Kalman filters
Maximum likelihood
Gas turbines
Turbines

Keywords

  • Finite impulse response filtering
  • Lagrange multiplier
  • robustness.
  • state estimation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Minimum Weighted Frobenius Norm Discrete-Time FIR Filter with Embedded Unbiasedness. / You, Sung Hyun; Ahn, Choon Ki; Shmaliy, Yuriy S.; Zhao, Shunyi.

In: IEEE Transactions on Circuits and Systems II: Express Briefs, 28.02.2018.

Research output: Contribution to journalArticle

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