Optimal Estimation of Clock Values and Trends From Finite Data

Charles Greenhall

Abstract:	We show how to solve two problems of optimal linear estimation from a finite set of phase data. Clock noise is modeled as a stochastic process with stationary dth increments. The covariance properties of such a process are contained in the generalized autocovariance function (GACV). We set up two principles for optimal estimation; these principles lead to a set of linear equations for the regression coefficients and some auxiliary parameters. The mean square errors of the estimators are easily calculated. The method can be used to check the results of other methods and to find good suboptimal estimators based on a small subset of the available data.
Published in:	Proceedings of the 37th Annual Precise Time and Time Interval Systems and Applications Meeting August 29 - 31, 2005 Vancouver, Canada
Pages:	377 - 382
Cite this article:	Greenhall, Charles, "Optimal Estimation of Clock Values and Trends From Finite Data," Proceedings of the 37th Annual Precise Time and Time Interval Systems and Applications Meeting, Vancouver, Canada, August 2005, pp. 377-382.
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