Continuous-time AR process parameter estimation in presence of additive white noise

Author

Fan, Haining ; Soderstrom, Torsten ; Zou, Yao

Author_Institution

Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH

Volume

47

Issue

12

fYear

1999

fDate

12/1/1999 12:00:00 AM

Firstpage

3392

Lastpage

3398

Abstract

Must existing work so far on continuous-time AR (CAR) parameter estimation concentrates on the noiseless measurement case. When measurement noise is present, our previous results on CAR parameter estimation need to be revised accordingly. Here we model the additive measurement noise as continuous-time white noise, and consider some approaches including average sampling and the direct LS method which we developed previously. Their advantages and disadvantages in this application are discussed

Keywords

autoregressive processes; continuous time filters; filtering theory; least squares approximations; low-pass filters; measurement; parameter estimation; signal sampling; white noise; CAR parameter estimation; additive white noise; anti-aliasing low pass filtering; average sampling; continuous time filtering; continuous-time AR process parameter estimation; continuous-time white noise; direct LS method; measurement noise; noiseless measurement; Additive white noise; Autoregressive processes; Filtering; Filters; Gaussian noise; Least squares methods; Noise measurement; Parameter estimation; Sampling methods; White noise;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.806082

Filename

806082