Andrich, C.C.AndrichEngelhardt, M.M.EngelhardtIhlow, A.A.IhlowBeuster, N.N.BeusterGaldo, G. delG. delGaldo2022-03-152022-03-152020https://publica.fraunhofer.de/handle/publica/41242410.1109/IFCS-ISAF41089.2020.9234818Traditional black box clock skew models are either the power-law noise model or a more recent approach based on auto-regressive (AR) filters. Unfortunately, neither algorithm can accurately model short and long term skew due to limited degrees of freedom or stability constraints. We propose a novel model that employs the current AR algorithm recursively with appropriate pre- and post-processing to achieve numeric stability and accurate reproduction of short and long term effects. The model coefficients are derived from a measured skew signal, with the model output matching an exemplary original signal closely in terms of Allan variance and time-domain behavior.en621006conference paper