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

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

doi:10.1109/TCSII.2018.2810812

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

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

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

7 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 language	English
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
DOIs	https://doi.org/10.1109/TCSII.2018.2810812
Publication status	Accepted/In press - 2018 Feb 28

Keywords

Finite impulse response filtering
Lagrange multiplier
robustness.
state estimation

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/TCSII.2018.2810812

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Cite this

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title = "Minimum Weighted Frobenius Norm Discrete-Time FIR Filter with Embedded Unbiasedness",

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.",

keywords = "Finite impulse response filtering, Lagrange multiplier, robustness., state estimation",

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AU - Ahn, Choon Ki

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AU - Zhao, Shunyi

PY - 2018/2/28

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N2 - 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.

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