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 1756-8412Full text not available in this repository. (Request a copy from the Strathclyde author)
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.
|Keywords:||nonlinear filtering, estimators, Kalman filters, Weiner filters, minimum variance filtering, medical signal processing, ball and beam experiment, filter design, Electrical engineering. Electronics Nuclear engineering, Control and Systems Engineering, Mechanical Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering|
|Depositing user:||Strathprints Administrator|
|Date Deposited:||18 Jun 2010 14:38|
|Last modified:||29 Apr 2016 00:54|