Iterative maximum likelihood estimation of the compound inverse Gaussian clutter parameters

Abstract

This Letter aims at proposing a cost-effective method for estimating the parameters of the compound inverse Gaussian distributed clutter. Under the assumption of the absence of thermal noise, an iterative maximum likelihood estimator (IMLE) is proposed and compared with existing MLE, the [zlog(z)] estimator, the non-integer order moments estimator and the higher order moment estimator. The results obtained show that the IMLE method outperforms all the other methods and has similar estimation performance than the MLE method but requires lower computational time.