NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
System identification approach applied to drift estimation
Published
Author(s)
Tracy S. Clement, Frans Verbeyst, Rik Pintelon, Yves Rolain, Johan Schoukens
Abstract
A system identification approach is applied to estimate the time base drift introduced by a high-frequency sampling oscilloscope. First, a new least squares estimator is proposed to estimate the delay of a set of repeated measurements in the presence of additive and jitter noise. Next, the effect of both additive and jitter noise is studied in the frequency domain using simulations. Special attention is devoted to the covariance matrix of the experiments, which is used to construct a weighted least squares estimator that minimizes the uncertainty of the estimated delays. Comparative results with respect to other state-of-the-art methods are shown. Finally, the enhanced method is applied to estimate the drift observed in repeated impulse response measurements of an optoelectrical converter using an Agilent 83480A sampling oscilloscope in combination with a 83484A 50 GHz electrical plug-in.
large-signal network analysis, sampling oscilloscopes, time base distortion, time base jitter, system identification, time base drift
Citation
Clement, T.
, Verbeyst, F.
, Pintelon, R.
, Rolain, Y.
and Schoukens, J.
(2007),
System identification approach applied to drift estimation, Proc., IEEE Instrum. Meas. Tech. Conf., Warsaw, 1, PL, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=32476
(Accessed October 17, 2025)