Detection and estimation of abrupt changes in Gaussian random processes with unknown parameters

In this study work we propose technically simple way of definition of the abrupt change in the power parameters of the band Gaussian processes, with the measurement of their values before and after the imbalance and in the conditions of parametric prior uncertainty. For this purpose, we found new approximations of solving statistics under various hypotheses, and performed their maximization in case of the unknown parameters, and also developed block diagrams of the corresponding detectors and measurers in the form of relatively simple single-channel devices. With help of the analytical (local Markov approximation) and statistical computer modeling methods, we established that offered detectors and measurers are efficient, and theoretical formulas for their characteristics well conform to the corresponding experimental data in a wide range of parameter values of the analyzed process.