Estimation of Time Variant System Clock Period for Wireless Sensor Network Applications

In industrial applications synchronized sensor nodes are vital for many tasks like multi parameter sampling of complex machinery behavior. The wirelessly connected nodes are usually synchronized to a base station. Therefore, frequency or period estimation of the reference clock is a key issue for all connected tasks like sampling, localization or applying energy optimized communication protocols. In wireless systems and especially in harsh industrial environments, it is likely to miss one or more synchronization events. The available data for clock estimations is therefore sparse and periodogramm estimators, at a complexity of at least O(N log N), are commonly used for accurate clock estimation. We introduce a period estimator for sparse clock signals with O(N) complexity. Furthermore, we present an equation for the observation time necessary to estimate the clock period at a certain quality. Mostly due to temperature influences, the crystal frequency at the nodes are varying. Our iterative period estimator follows those changes with a given estimation accuracy. We analyze an equation, which allows to calculate the accuracy of the estimator given a certain change rate of time variant system clock. The work is concluded with simulations considering sparse and time varying processes, including a discussion of the application of the method.