Maximum likelihood estimation of aperture jitter using sinusoidal excitation

This paper proposes a solution to estimate the aperture jitter of analog-to-digital (ADCs) converters using the maximum likelihood (ML) approach. The idea is to extend the model built for the ML estimation of ADC and excitation signal parameters to handle the uncertainty of sampling. Using the Gaussian model of aperture jitter this extension requires only one additional parameter. This research article investigates the feasibility of this extension, gives the extended likelihood function in closed form and proposes a slight approximation to decrease computational demand significantly. The increased explanatory power of the extended model is shown via evaluation of simulated and real measurements.