Recursive fixed-interval smoother with correlated signal and noise in presence of uncertain observations

Author

Nakamori, S. ; Hermoso-Carazo, A. ; Linares-Pérez, J. ; Sánchez-Rodríguez, M.I.

Author_Institution

Dept. of Technol., Kagoshima Univ., Japan

Volume

2

fYear

2003

fDate

18-20 Sept. 2003

Firstpage

854

Abstract

A recursive filter and fixed-interval smoother are presented in this paper, using observations which are affected by additive and multiplicative noises; additive noise is a white process correlated with signal and multiplicative one is modelled by independent Bernoulli random variables. It is used an innovation approach and assumed that the autocovariance function of signal and the crosscovariance function about signal and observation noise are expressed in a semidegenerate kernel form. The algorithms are obtained using covariance information of signal and observation noise, without using the state-space model.

Keywords

discrete time filters; least squares approximations; recursive filters; smoothing methods; additive noise; autocovariance function; crosscovariance function; fixed-interval smoother; independent Bernoulli random variable; multiplicative noise; recursive filter; semidegenerate kernel form; Additive noise; Equations; Kernel; Nonlinear filters; Random variables; Signal processing; Signal processing algorithms; Smoothing methods; State estimation; Technological innovation;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on

Print_ISBN

953-184-061-X

Type

conf

DOI

10.1109/ISPA.2003.1296398

Filename

1296398