Low-order moment-based estimation of shape parameter of CGIG clutter model

In this Letter, a low-order moment-based estimation of the parameters of compound-Gaussian clutter model with the inverse Gaussian texture (CGIG) is proposed. The CGIG clutter model proposed recently was known as an effective model to describe high-resolution sea clutter at low grazing angles. Its parameter estimation is often obtained by the explicit moment-based estimation using the second- and fourth-order moments, which is low precision in the case of small samples. Here, the first- and second-order moments are used to construct a higher precision estimator, where the look-up table method is employed to make up the lack of explicit expression of the shape parameter.