Computational Study of Data Generated During Time-Domain Overlapping Processes

Determination of the frequency from a given signal is a task that is required in diverse systems, which range from instrumentation of sensors to more advance systems such as radars. There are diverse methods for estimation of an undetermined frequency, some of these include direct counting, time averaging or more sophisticated methods that use algorithms based on the fast Fourier Transform (FFT). For modern instrumentation systems, transduction process from frequency to digital domain is a process that is required to be integrated into sensors or at monolithic level in the integrated systems. This is a characteristic that defines what kind of algorithm for frequency estimation can be used. Highly complicated measurement techniques require specialized circuits that need long time for achieving good approximations, and also, if complex computational tasks are required, the power consumption increases during the measurement time. The principle of rational approximations has proved to be a method for frequency approximation where the desired frequency is approximated in a short time after the use relatively simple circuits. In this work, the principle of rational approximations is implemented for measuring the frequency of a signal and the resulting data is studied. This with the aim of assessing the characteristics of data during the measurement process.