National University of Oil and Gas "Gubkin University", 65, Bld. 1 Leninsky Prospekt, Moscow, Russia, 119991.
School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC, 3001, Australia.
Sci Rep. 2022 Nov 19;12(1):19932. doi: 10.1038/s41598-022-24457-2.
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.
本文致力于基于完全充分统计量方法和使用 Lehmann-Scheffe 定理的可能性来合成新的信号处理算法。通过准矩形脉冲序列的示例,说明了考虑占空比因子和脉冲方形系数来估计其周期的方法。在此基础上,开发了一个数学模型,基于该模型,对方法的潜在精度进行了估计。结果表明,对于样本大小值(n > 8),使用完全充分统计量方法估计重复周期的相对均方根误差低于传统估计的误差。除了理论计算,还给出了证实所获得效果的模拟结果。所得到的结果具有广泛的适用性,可用于石油和天然气行业的控制和测量设备的设计、医疗设备的开发、电信领域、脉冲多普勒雷达的设计等。