Parameter Estimation of Rayleigh-Generalized Gamma Mixture Model

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dc.contributor.authorAhmed, Bentoumi
dc.contributor.authorAmar, Mezache
dc.contributor.authorHoucine, Oudira
dc.date.accessioned2020-12-27T09:36:40Z
dc.date.available2020-12-27T09:36:40Z
dc.date.issued2019-12
dc.description.abstractThe estimation problem of three parameters Rayleigh-Generalized Gamma Mixture (R-GG) radar clutter model is addressed in this paper. Expressions of integer order moments, non-integer order moments and logarithmic moments are presented in such away the scale parameter of the R-GG probability density function (PDF) is eliminated and a two-dimensional estimators labeled HOME, NIOME and [zlog(z)] methods are obtained. Due to the presence of gamma function with fractional variables, these estimators cannot be given in closed forms. The fitness function for each estimator is given as a sum of squared errors of nonlinear equations. Using a numerical routine based upon the simplex search algorithm, the proposed methods were tested firstly on artificial data. Tail fitting of the R-GG model and the standard K-distribution (i.e., special case of the R-GG) is assessed against recorded radar data. The accuracy of the R-GG model and the proposed estimation methods is satisfactory, with the most accuracy of the [zlog(z)] method.en_US
dc.identifier.urihttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/22713
dc.publisherUniversité de M'silaen_US
dc.subjectradar clutter, parameter estimation, compound-gaussian, generalized gamma, HOME, NIOME, [zlog(z)]en_US
dc.titleParameter Estimation of Rayleigh-Generalized Gamma Mixture Modelen_US
dc.typeArticleen_US

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