Averaging sampling: Models and properties

In the paper we study the properties of a sampling method for stochastic signals corrupted by a wide-band stochastic noise where samples are taken as average values of the signal over the sampling interval to diminish the influence of noise. We also study possible improvement attained by discrete-time Kalman filtering applied to the sampled signal. We compare the results with two competitive methods: classical point-wise sampling followed by discrete-time filtering, and continuous-time Kalman filtering prior to sampling possibly followed by digital filtering. The study is performed for a wide range of sampling periods and noise-to-signal ratios and leads to important practical conclusions.