In this paper we estimate finite mixture models (FMM) to describe the statistics of the ultrawideband (UWB) channel
amplitudes. Various combinations of Rayleigh, Nakagami, Weibull, and Lognormal distributions are used to form the
constituent probability density functions (PDFs) of the FMMs. The FMMs are identified using the Stochastic
Expectation Maximization (SEM) algorithm. Akaike's Information Criterion is used to compare the quality of data fit
provided by the FMMs and models containing only one distribution (non-mixtures). The results indicate that UWB
channel amplitude statistics are best represented by mixtures of Rayleigh, Lognormal and Weibull PDFs.