Recursive estimation of K-distribution parameters

We address the problem of estimating parameters of K-distribution. A recursive procedure based on the recursive EM algorithm is derived to find the ML estimates. Recursive EM is a stochastic approximation procedure with a gain matrix derived from the augmented data. Under mild conditions estimates generated by such procedure are characterized by strong consistency and asymptotic normality. Because of the simple structure of the augmented data, the proposed algorithm has a simple implementation. Numerical results show that the proposed approach performs well for various parameter sets.