Abstract. In this report, statistical signal properties are analysed and aGaussian process model is developed for scenarios with a moving receiver ina scattering environment, as in Clarke’s model, with the generalisation thatnoise is introduced through scatterers randomly flipping on and off as a functionof time. The Gaussian process model is developed by extracting meanand covariance properties from the Multipath Fading Channel model (MFC).That is, we verify that under certain assumptions, signal realisations of theMFC model converge to a Gaussian process and thereafter compute the Gaussianprocess’ covariance matrix, which is needed to construct Gaussian processsignal realisations. The obtained Gaussian process model is, under certainassumptions, less computationally costly, contains more channel informationand has very similar signal properties to its corresponding MFC model. Theproblem of fitting our model’s flip rate and scatterer density to measured signaldata is also studied.