Generation of Non-Gaussian Wide-Sense Stationary Random Processes with Desired PSDs and PDFs

This paper describes a new method to generate discrete signals with arbitrary power spectral density (PSD) and first order probability density function (PDF) without any limitation on PDFs and PSDs. The first approximation has been achieved by using a nonlinear transform function. At the second stage the desired PDF was approximated by a number of symmetric PDFs with defined variance. Each one provides a part of energy from total signal with different ratios of remained desired PSD. These symmetric PDFs defined by sinusoidal components with random amplitude, frequency and phase variables. Both analytic results and examples areincluded. The proposed scheme has been proved to be useful in simulations involving non-Gaussian processes with specific PSDs and PDFs.