Computationally efficient estimation of compound K-distribution sea clutter in thermal noise and its application to sea echo reflectivity observations

We consider the parameter estimation of the K-plus-noise distribution model of sea clutter intensity single-pulse observations with unknown thermal noise power. We propose two methods that yield comparable estimation accuracy to existing methods while improving computational cost for real-time processing. These methods iteratively integrate one-dimensional nonlinear curve fitting with integer and fractional intensity moment computations. We provide numerically computed Cramér-Rao lower bounds for the shape estimate as a bench mark for asymptotically unbiased estimators. Performance is demonstrated using simulations and two high-resolution sea echo reflectivity datasets.