State estimation in the presence of non-Gaussian noise

Author

Plataniotis, K.N. ; Venetsanopoulos, A.N.

Author_Institution

Toronto Univ., Ont., Canada

fYear

2000

fDate

2000

Firstpage

230

Lastpage

235

Abstract

The problem of nonlinear filtering with a non-Gaussian model of measurement errors is considered. Based on Bayes classification of the observations an approximate solution is introduced. The Bayesian estimator can be applied to any discrete time, linear, or nonlinear system which is observed in additive non-Gaussian measurement noise. The problem of narrowband interference suppression in additive noise is considered as an important example of non-Gaussian noise filtering. It is shown that the approximate filter outperforms currently used approaches and at the same time offers simplicity in the design

Keywords

Bayes methods; approximation theory; filtering theory; interference suppression; measurement errors; noise; nonlinear filters; parameter estimation; radiofrequency interference; signal classification; spread spectrum communication; state estimation; Bayes classification; Bayesian estimator; DS-SS; additive nonGaussian measurement noise; approximate filter; approximate solution; direct sequence spread spectrum; discrete time system; impulsive channels; linear system; measurement errors; narrowband interference suppression; nonGaussian model; nonGaussian noise filtering; nonlinear filtering; nonlinear system; state estimation; Additive noise; Bayesian methods; Filtering; Interference suppression; Measurement errors; Narrowband; Noise measurement; Nonlinear systems; State estimation; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000

Conference_Location

Lake Louise, Alta.

Print_ISBN

0-7803-5800-7

Type

conf

DOI

10.1109/ASSPCC.2000.882476

Filename

882476