Order statistic fast Kalman filter

Author

Settineri, R. ; Najim, M. ; Ottaviani, D.

Author_Institution

ENSERB, Domaine Univ., France

Volume

2

fYear

1996

fDate

12-15 May 1996

Firstpage

116

Abstract

This paper deals with the derivation of a new adaptive filtering algorithm, which takes into consideration the often encountered case of impulsive perturbations. The proposed method is a combination of a RLS-based algorithm and the Order Statistic (OS) filter, and can be seen as an extension of the LMS-type Order Statistic filter (OSLMS). In order to obtain a computational burden comparable to the OSLMS filter, our derivation is based on a fast version of the RLS algorithm-the Fast Kalman filter. We will show that the new algorithm is not a coarse extension of the OSLMS filter and that care should be taken when performing the order statistic filtering operation

Keywords

adaptive Kalman filters; least mean squares methods; median filters; recursive filters; OSLMS filter; RLS algorithm; adaptive filtering algorithm; impulsive perturbations; order statistic fast Kalman filter; Adaptive algorithm; Adaptive filters; Additive noise; Filtering algorithms; Image processing; Interference; Least squares approximation; Nonlinear filters; Resonance light scattering; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on

Conference_Location

Atlanta, GA

Print_ISBN

0-7803-3073-0

Type

conf

DOI

10.1109/ISCAS.1996.540366

Filename

540366