Unbiased FIR Filtering for Time-Stamped Discretely Delayed and Missing Data

Karen J. Uribe-Murcia; Yuriy S. Shmaliy; Choon Ki Ahn; Shunyi Zhao

doi:10.1109/TAC.2019.2937850

Unbiased FIR Filtering for Time-Stamped Discretely Delayed and Missing Data

Karen J. Uribe-Murcia, Yuriy S. Shmaliy, Choon Ki Ahn, Shunyi Zhao

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

15 Citations (Scopus)

Abstract

The unbiased finite impulse response (UFIR) filtering approach is developed for discrete-time state-space models with time-stamped discretely delayed and missing data. The model with k-step-lags in observations is transformed to have no latency and expanded on a finite horizon of N most recent data points. It is shown that the optimal horizon for the UFIR filter is practically k-invariant, unlike the tuning factor of the H_&inf; filter. Higher robustness of the UFIR filter against the Kalman and H_&inf; filters is justified theoretically in uncertain environments with discretely delayed and missing data. Experimental verification is provided based on GPS-based tracking of a moving vehicle to demonstrate a good agreement with the theory.

Original language	English
Article number	8815824
Pages (from-to)	2155-2162
Number of pages	8
Journal	IEEE Transactions on Automatic Control
Volume	65
Issue number	5
DOIs	https://doi.org/10.1109/TAC.2019.2937850
Publication status	Published - 2020 May

Keywords

Delayed data
H&inf; filter
Kalman filter (KF)
robustness
unbiased finite impulse response (FIR) filter

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TAC.2019.2937850

Cite this

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title = "Unbiased FIR Filtering for Time-Stamped Discretely Delayed and Missing Data",

abstract = "The unbiased finite impulse response (UFIR) filtering approach is developed for discrete-time state-space models with time-stamped discretely delayed and missing data. The model with k-step-lags in observations is transformed to have no latency and expanded on a finite horizon of N most recent data points. It is shown that the optimal horizon for the UFIR filter is practically k-invariant, unlike the tuning factor of the H&inf; filter. Higher robustness of the UFIR filter against the Kalman and H&inf; filters is justified theoretically in uncertain environments with discretely delayed and missing data. Experimental verification is provided based on GPS-based tracking of a moving vehicle to demonstrate a good agreement with the theory.",

keywords = "Delayed data, H&inf; filter, Kalman filter (KF), robustness, unbiased finite impulse response (FIR) filter",

author = "Uribe-Murcia, {Karen J.} and Shmaliy, {Yuriy S.} and Ahn, {Choon Ki} and Shunyi Zhao",

note = "Funding Information: Manuscript received November 23, 2018; revised November 27, 2018 and March 4, 2019; accepted August 19, 2019. Date of publication August 27, 2019; date of current version April 23, 2020. The work of K. J. Uribe-Murcia and Y. S. Shmaliy was supported by the Mexican CONACyT-SEP Project A1-S-10287, convocatoria 2017–2018. The work of C. K. Ahn was supported by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. Recommended by Associate Editor S. S. Saab. (Corresponding author: Yuriy S. Shmaliy.) K. J. Uribe-Murcia and Y. S. Shmaliy are with the Department of Electronics Engineering, Universidad de Guanajuato, Salamanca 36885, Mexico (e-mail:,karen.uribe15@gmail.com; shmaliy@ugto.mx). Publisher Copyright: {\textcopyright} 1963-2012 IEEE.",

year = "2020",

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AU - Zhao, Shunyi

N1 - Funding Information: Manuscript received November 23, 2018; revised November 27, 2018 and March 4, 2019; accepted August 19, 2019. Date of publication August 27, 2019; date of current version April 23, 2020. The work of K. J. Uribe-Murcia and Y. S. Shmaliy was supported by the Mexican CONACyT-SEP Project A1-S-10287, convocatoria 2017–2018. The work of C. K. Ahn was supported by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. Recommended by Associate Editor S. S. Saab. (Corresponding author: Yuriy S. Shmaliy.) K. J. Uribe-Murcia and Y. S. Shmaliy are with the Department of Electronics Engineering, Universidad de Guanajuato, Salamanca 36885, Mexico (e-mail:,karen.uribe15@gmail.com; shmaliy@ugto.mx). Publisher Copyright: © 1963-2012 IEEE.

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AB - The unbiased finite impulse response (UFIR) filtering approach is developed for discrete-time state-space models with time-stamped discretely delayed and missing data. The model with k-step-lags in observations is transformed to have no latency and expanded on a finite horizon of N most recent data points. It is shown that the optimal horizon for the UFIR filter is practically k-invariant, unlike the tuning factor of the H&inf; filter. Higher robustness of the UFIR filter against the Kalman and H&inf; filters is justified theoretically in uncertain environments with discretely delayed and missing data. Experimental verification is provided based on GPS-based tracking of a moving vehicle to demonstrate a good agreement with the theory.

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Unbiased FIR Filtering for Time-Stamped Discretely Delayed and Missing Data

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Keywords

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