Nakagami Distribution Parameters Comparatively Estimated by the Moment and Maximum Likelihood Methods

Abstract

Probability distribution density parameters determined using the maximum likelihood and moment methods are comparatively estimated according to their accuracy and complexity of estimation algorithms. Expressions determining the Nakagami distribution parameters by the maximum likelihood method are obtained. A method for estimating the Nakagami distribution parameters by the moment method in which the distribution moments are replaced by their estimates is described. It is noted that parameter estimation by the maximum likelihood method has a smaller variance and bias as compared to estimation by the moment method, especially with a small sample size. It is shown that, unlike energy parameter estimation, the real laws of Nakagami distribution are approximated using a large volume of statistical data that describe the signal.