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This letter addresses high-resolution sea clutter modelling. Radar clutter modelling is essential to develop constant false alarm rate (CFAR) detection schemes. In this paper, we propose a compound model by the use of the inverted exponentiated Rayleigh (IER) distribution as texture component. The probability density function (PDF) of the compound inverted exponentiated Rayleigh (CIER) distribution is a function of three parameters including the thermal noise power. To assess the modelling performance of the CIER distribution, several tests have been performed using the Intelligent PIXel Processing Radar (IPIX) database where the fitted PDFs and the complimentary cumulative density functions (CCDFs) of the CIER, the well-known compound K and the compound inverse Gaussian (CIG) distributions are compared with the real PDF and CCDF. The results obtained validate the ability of the CIER distribution to model high-resolution sea clutter. [ABSTRACT FROM AUTHOR]

The estimation of the K-distributed radar clutter plus thermal noise parameters can be improved by employing fractional moments instead of the existing higher order moments. In order to achieve this, we provide first an asymptotic expression of the moments in terms of the confluent and Gauss hypergeometric functions. For fractional orders of the latter, the new estimation method is derived so that the estimates of the shape parameter are achieved via numerical computations of nonlinear equations. For lower fractional orders of moments and different values of the parameters, the numerical simulations demonstrate the effectiveness of the proposed estimation procedure when compared with the standard higher order moments method. [ABSTRACT FROM AUTHOR]

A statistical model for high-resolution sea clutter, which we have called the compound inverse Gaussian (CIG) distribution, is proposed. The model is a mixture of the Rayleigh distribution and the inverse Gaussian (IG) distribution to model the speckle and the texture components, respectively. The CIG probability density function (pdf) is generalized to account for the additive thermal noise to achieve a good match to real data. The overall pdf is given in an integral form as a function of three parameters which are estimated from the recorded data based on the parametric curve-fitting estimation (PCFE) method of the complementary cumulative distributed function (CCDF). The Nelder-Mead (N-M) simplex algorithm is used to provide the best estimates of the pdf parameters. Using the IPIX backscatter database, the fitting of the CIG pdfs and the cumulative distributed functions (cdfs) are assessed and compared with the fitted Weibull, log-normal, Rician inverse Gaussian (RiIG), K plus noise, compound log-normal (CLN), and Pareto plus noise distributions. Experimental fitting results show that the sea-clutter amplitudes obey the proposed CIG model in most cases. [ABSTRACT FROM AUTHOR]