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Application of Mellin Kind Statistics to Polarimetric G Distribution for SAR Data

Khan, SS and Guida, R (2014) Application of Mellin Kind Statistics to Polarimetric G Distribution for SAR Data IEEE Transactions on Geoscience and Remote Sensing. pp. 3513-3528.

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Abstract

The ${cal K}$ distribution can arguably be regarded as one of the most successful and widely used models for radar data. However, in the last two decades, we have seen tremendous growth in even more accurate modeling of radar statistics. In this regard, the relatively recent ${cal G}^{0}$ distribution has filled some deficiencies that were left unaccounted for by the ${cal K}$ model. The ${cal G}^{0}$ model, in fact, resulted as a special case of a more general model, the ${cal G}$ distribution, which also has the ${cal K}$ model as its special form. Single-look and multilook complex polarimetric extensions of these models (and many others) have also been proposed in this prolific era. Unfortunately, statistical analysis using the polarimetric ${cal G}$ distribution remained limited, primarily because of more complicated parameter estimation. In this paper, the authors have analyzed the ${cal G}$ model for its parameter estimation using state-of-the-art univariate and matrix-variate Mellin-kind statistics (MKS). The outcome is a class of estimators based on the method of log cumulants and the method of matrix log cumulants. These estimators show superior performance characteristics for product model distributions such as the ${cal G}$ model. Diverse regions in TerraSAR-X polarimetric synthetic aperture radar data have also been statistically analyzed using the ${cal G}$ model with its new and old estimators. Formal goodness-of-fit testing, based on the MKS theory, has been used to assess the fitting accuracy between different estimators and also between the ${cal G}$, ${cal K}$, ${cal - }^{0}$, and Kummer-${cal U}$ models.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Surrey Space Centre
Authors :
AuthorsEmailORCID
Khan, SSUNSPECIFIEDUNSPECIFIED
Guida, RUNSPECIFIEDUNSPECIFIED
Date : 1 June 2014
Identification Number : 10.1109/TGRS.2013.2273176
Additional Information : 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Depositing User : Symplectic Elements
Date Deposited : 23 Jul 2013 09:07
Last Modified : 06 May 2015 13:33
URI: http://epubs.surrey.ac.uk/id/eprint/790070

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