A New Method for Estimating the Power Spectrum of a Stationary Random Signal Based

It is proposed to use reduction rulers to estimate the autocorrelation function and the power spectrum of a stationary random signal for a finite sample for different variants of non-uniform data sampling. Various methods of its construction are analyzed, both according to the well-known Golomb ruler and convenient for practical application of the line using non-uniform data sampling with switching the sampling frequency at two close frequencies. The results of numerical modeling of the accuracy of the signal power spectrum estimation using standard deviation are presented.