23rd International Conference on
Circuits, Systems, Communications and Computers
(CSCC 2019),
Marathon Beach, Athens, July 14-17, 2019          www.cscc.co    Contact us

 
Conference
 
 

Plenary Speaker

Unbiased State Estimation: An Alternative to Kalman Filtering with Improved Robustness

Professor Yuriy S. Shmaliy

Universidad de Guanajuato

Department of Electronics Engineering

DICIS, Salamanca, 36885, Mexico

E-mail: shmaliy@ugto.mx


Abstract: If a system and its observation are both represented in state space with linear equations, the system noise and the measurement noise are white, Gaussian, and mutually uncorrelated, and the system and measurement noise statistics are known exactly, then the optimal Kalman filter (KF) provides the best state estimate. However, the KF performance may be poor if operational conditions are far from ideal. Researchers are aware of the numerous issues facing the use of the KF in practice: insufficient robustness against mismodeling and temporary uncertainties, the strong effect of the initial values, and high vulnerability to errors in the noise statistics. Under such conditions, better performances demonstrate unbiased state estimators, which completely ignore the noise statistics, except for the zero mean assumption, and initial values. Due to these features, the unbiased finite impulse response (UFIR) filter is known to be more robust than the KF. The only tuning factor required by the UFIR filter is the averaging horizon of N points. However, much smaller efforts are required to find an optimal Nopt than for the noise statistics and initial values. Furthermore, because the UFIR filter ignores noise in the algorithm, UFIR smoothing with lag q > 0 can easily be organized as the backward prior estimate. In this lecture, the state-of-the-art iterative UFIR filtering algorithms are reviewed for time-varying linear and nonlinear systems represented in state space. A comparison with the KF is also provided along with several practical examples of applications.

Brief Biography of the Speaker: Dr. Yuriy S. Shmaliy has been a full professor in Electrical Engineering of the Universidad de Guanajuato, Mexico, since 1999. He received the B.S., M.S., and Ph.D. degrees in 1974, 1976 and 1982, respectively, from the Kharkiv Aviation Institute, Ukraine. In 1992 he received the Dr.Sc. (technical) degree from the Kharkiv Railroad Institute. In March 1985, he joined the Kharkiv Military University. He serves as full professor beginning in 1986 and has a Certificate of Full Professor, since 1993. In 1993, he founded and, by 2001, had been a director of the Scientific Center “Sichron” (Kharkiv, Ukraine) working in the field of precise time and frequency. His books Continuous-Time Signals (2006) and Continuous-Time Systems (2007) were published by Springer, New York. His book GPS-based Optimal FIR Filtering of Clock Models (2009) was published by Nova Science Publ., New York. He also edited a book Probability: Interpretation, Theory and Applications (Nova Science Publ., New York, 2012) and contributed to several books with invited chapters. Dr. Shmaliy has authored 436 Journal and Conference papers and holds 81 patents. He is IEEE Fellow; was rewarded a title, Honorary Radio Engineer of the USSR, in 1991; was listed in Outstanding People of the 20th Century, Cambridge, England in 1999; and was granted with the Royal Academy of Engineering Newton Collaboration Program Award in 2015. He has been a visiting professor-researcher in City University London in 2015-2016 and in TELECOM SudParis in 2015, 2017 and 2018. He was invited many times to give tutorial, keynote, and plenary lectures. He currently serves on the Editorial Boards of several International Journals and is a member of the Program Committees of various Int. Symposia. His current interests include statistical signal processing, optimal estimation, and stochastic system theory.