This paper is devoted to the synthesis of new signal processing algorithms based on the methodology of complete sufficient statistics and the possibility of using the Lehmann–Scheffe theorem. Using the example of a sequence of quasi-rectangular pulses, an approach to estimating their period was illustrated, taking into account the duty-off factor and the pulse squareness coefficient. A mathematical model was developed, on the basis of which, estimates of the potential accuracy of the methods were carried out. It is established that for the sample size value (n > 8), the relative root-mean-square error of estimating the repetition period using the methodology of complete sufficient statistics is lower than that of the traditional estimate. In addition to theoretical calculations, simulation results confirming the achieved effect are presented. The results obtained have a wide range of applicability and can be used in the design of control and measuring equipment in the oil and gas industry, in the development of medical equipment, in the field of telecommunications, in the design of pulse-Doppler radars, etc.

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ࣧ Using a model of a sequence of quasi-rectangular pulses as an example, an approach was illustrated to assess their period, taking into account the off-duty factor and the squareness coefficient of the pulses. Complete sufficient statistics (CSS) methodology was used. An analytical expression for the pulse repetition was presented. It was shown that for the value of the sample size (n > 8) the relative root-mean square error of the repetition period estimation by CSS is shown as a significantly smaller error than that of the traditional estimate, which is only asymptotically effective. In addition to theoretical calculations, simulation results confirming the achieved effect are presented. The results obtained are applicable for the design of the control and measuring equipment of the oil and gas industry.