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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including those from the School of Psychological Sciences & Health - but also papers by researchers based within the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

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Design and implementation of non-linear minimum variance filters

Naz, Shamsher Ali and Grimble, M.J. (2009) Design and implementation of non-linear minimum variance filters. International Journal of Advanced Mechatronic Systems, 1 (4). pp. 233-241. ISSN 1756-8412

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Abstract

The non-linear minimum variance (NMV) filtering problem for a non-linear multi-input and multi-output (MIMO) discrete-time system is considered. The NMV filter is designed to minimise a minimum variance criterion. The system model includes channel non-linearities that may be treated as a black box. The NMV filter can avoid the need for a linearisation stage that is required in the extended Kalman filter (EKF). The MIMO NMV filter algorithm is easy to implement, in comparison to the EKF. The main contribution of this paper lies in the design and evaluation of the NMV algorithm for the non-linear MIMO filtering problem. A case study is used to demonstrate performance that is based upon a problem in the medical signal processing area. The design and the real time implementation of the NMV estimator is also considered, for a laboratory based ball and beam experiment. The performance is compared with that of an EKF and real time implementation of both estimators is discussed.