Simulation Statistical Model of Reflection from the “Clear-Sky”

Statistical Models of the Troposphere Refractive Index

“…it, in its turn, is caused by the spatial and temporal distribution of the refractive index N. Therefore, the study of seasonal, diurnal and vertical distribution of N, making of its statistical model provides the great interest to predict the range of the radio systems for various applications, as well as estimates of the accuracy of measuring the coordinates of global navigation satellite systems (GNSS). Productive, at the same time may be the approach which was used earlier to describe the space-time non-stationary signals scattered underlying surfaces and "clear" sky using nested semi-Markov processes [1,2].…”

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

“…With high resolution in range and angular coordinates, there are significant deviations of fluctuation distribution of signals reflected by underlying surfaces and by the "clear" sky from the standard ones [1,2]. This is due to sequential and separate observation of surface regions with different statistical properties of irregularities, which generate nonstationary and non-Gaussian scattered signals, as well as the atmosphere areas being significantly different from standard ones by the refractive index [1,2].…”

“…This is due to sequential and separate observation of surface regions with different statistical properties of irregularities, which generate nonstationary and non-Gaussian scattered signals, as well as the atmosphere areas being significantly different from standard ones by the refractive index [1,2]. The non-Gaussian scattered signals were accounted historically by models providing the specified statistics using the nonlinear inertialess transformation of a random process by the Gaussian distribution law [3].…”