Using embedded semi-Markov processes for describing nonstationary signals and fields

The possibility of using embedded semi-Markov processes for creating statistical models of signals reflected from the interface (land-sea) as well as from areas of the “clear” sky is considered in the given work. And parameters of these areas are identified on the basis of experimental data. It is shown that the nonstationarity of seasonal changes in the troposphere refractive index can be accounted for by describing its statistics by poly-Gaussian models. Model parameters for each season are derived experimentally. The proposed approach can be used to create a simulation model of the refractive index behavior using embedded semi-Markov processes.