Title :
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
fDate :
12/1/1999 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
