Title: Design and implementation of non-linear minimum variance filters

Authors: Shamsher Ali Naz, M.J. Grimble

Addresses: University of Strathclyde, Industrial Control Centre, Graham Hills Building, 50 George Street, Glasgow, G1 1QE, UK. ' University of Strathclyde, Industrial Control Centre, Graham Hills Building, 50 George Street, Glasgow, G1 1QE, UK

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.

Keywords: nonlinear filtering; estimators; Kalman filters; Weiner filters; minimum variance filtering; medical signal processing; ball and beam experiment; filter design.

DOI: 10.1504/IJAMECHS.2009.026328

International Journal of Advanced Mechatronic Systems, 2009 Vol.1 No.4, pp.233- 241

Available online: 06 Jun 2009 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article