Estimation and analysis of noise error on digital sampling
Zhang Hua · 2007
This paper presented a ML estimator for the estimation of high-frequency sampling noise model to solve the problem that high-frequency sampling suffer from both additive noise and time jitter error estimation.After deriving the mathematical equations,a comparison between the LS and the ML estimators was performed.Simulation results show that the ML estimator produces more efficient than the LS estimator.In addition,it has the advantage that the Cramer-Rao lower bound can be used as an uncertainty bound on the estimation.