@article{d47484aa6c514982ad7e76387228a78f,
title = "Self-Tuning Unbiased Finite Impulse Response Filtering Algorithm for Processes with Unknown Measurement Noise Covariance",
abstract = "An unbiased finite impulse response (UFIR) filtering algorithm is designed in the discrete-time state-space for industrial processes with unknown measurement data covariance. By assuming an inverse-Wishart distribution, the data noise covariance is recursively estimated using the variational Bayesian (VB) approach. The optimal averaging horizon length Nopt is estimated in real time by incorporating the estimated data noise covariance into the full-horizon UFIR filter and specifying Nopt at a point, where the estimation error covariance reaches a minimum. The proposed VB-UFIR algorithm is applied to a quadrupled water tank system and moving target tracking. It is demonstrated that the VB-UFIR filter self-estimates Nopt more accurately than known solutions. Furthermore, the VB-UFIR filter is not prone to divergence and produces more stable and more reliable estimates than the VB-Kalman filter.",
keywords = "Averaging horizon, Kalman filter (KF), state estimation, unbiased finite impulse response (UFIR) filter, variational Bayesian (VB) approach",
author = "Shunyi Zhao and Shmaliy, {Yuriy S.} and Ahn, {Choon Ki} and Fei Liu",
note = "Funding Information: Manuscript received January 16, 2020; accepted April 24, 2020. Date of publication May 11, 2020; date of current version April 12, 2021. Manuscript received in final form April 27, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61973136, Grant 61991402, and Grant 61833007, in part by the 111 Project under Grant B12018, in part by the Alexander von Humboldt Foundation, in part by the Mexican CONACyT-SEP Project A1-S-10287 under Grant CB2017-2018, and in part by the National Research Foundation of Korea Grant funded by the Korea Government, Ministry of Science and ICT, under Grant NRF-2020R1A2C1005449. Recommended by Associate Editor M. A. Grover. (Corresponding authors: Shunyi Zhao; Yuriy S. Shmaliy.) Shunyi Zhao is with the Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi 214122, China, and also with the Automatic Control and Complex Systems, University of Duisburg-Essen, 47057 Duisburg, Germany (e-mail: shunyi.s.y@ gmail.com). Publisher Copyright: {\textcopyright} 1993-2012 IEEE.",
year = "2021",
month = may,
doi = "10.1109/TCST.2020.2991609",
language = "English",
volume = "29",
pages = "1372--1379",
journal = "IEEE Transactions on Control Systems Technology",
issn = "1063-6536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",
}