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Mellin Transform-Based Approach for Parameter Estimation of K Distribution Plus Noise

Mellin transform is a fast and robust method for parameter estimation. In this paper, the parameter estimator of K plus noise (KpN) model based on the Mellin transform is proposed. First, we start deriving the expression of the second characteristic functions and log-based moments in detail by Mellin transform. And then, we provide the expression of the first fourth order log-culumants which are directly related to the parameters of KpN model. Finally, the numerical computation is applied to realize parameter estimation of KpN model. The Monte Carlo simulations show that the proposed estimator is more efficient than existing methods for clutter to noise ratios under both situations of large and small sample sizes.