Fitting a statistical model to SIR-C SAR images of the sea surface

Author

Fusco, Adele ; Galdi, Carmela ; Ricci, Giuseppe ; Tesauro, Manlio

Author_Institution

Dipt. di Ingegneria, Universita degli Studi del Sannio, Benevento, Italy

Volume

40

Issue

4

fYear

2004

Firstpage

1179

Lastpage

1190

Abstract

A suite of statistical procedures aimed at assessing to what extent polarimetric and/or multifrequency synthetic aperture radar (SAR) images of the sea surface can be modeled in terms of spherically invariant random vectors and matrices (SIRVs and SIRMs) is presented. The proposed tests assume that images can be described by resorting to the compound-Gaussian model, but do not require any a priori knowledge about the actual first-order probability density function (pdf) of the texture. The tests have also been used to analyze three data sets from STR-C/X-SAR missions.

Keywords

geophysical signal processing; oceanographic techniques; radar imaging; remote sensing by radar; statistical analysis; synthetic aperture radar; SIR-C SAR images; compound-Gaussian model; multifrequency synthetic aperture radar; polarimetric synthetic aperture radar; probability density function; sea surface; spherically invariant random matrices; spherically invariant random vectors; statistical model; Algorithm design and analysis; Data analysis; Detection algorithms; Frequency; Petroleum; Probability density function; Sea surface; Surface fitting; Synthetic aperture radar; Testing;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2004.1386873

Filename

1386873