Publisher:Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2005.
Citation:Joint International Frequency Control Symposium and Precise Time and Time Interval (PTTI) Systems and Applications Meeting, Vancouver, British Colombia, Canada, August 29, 2005.
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: with the help of the GACV, 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
