Statistical Non-Gaussian Model of Sea Surface With Anisotropic Spectrum for Wave Scattering Theory. Part I - Abstract

Tatarskiǐ, V. I.; Tatarskii, V. V.

doi:10.1163/156939399x00385

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…However, the PDF with the final number of cumulant does not exist and it leads to appearance of negative probabilities [1], immediately relating to calculating the RCS. Describing the Non-Gaussian multivariate PDF instead of Gram-Charlier series, this article use decomposition of arbitrary PDF in the sum of an auxiliary multivariate Gaussian PDF putting forward by V. Tatarskii [2][3][4][5]. It allows obtain the scattering cross section in the Kirchhoff and other approximations for Non-Gaussian surfaces with the Elfouhaily spectrum and the PDF of the principal slopes.…”

Section: Introductionmentioning

confidence: 99%

Decomposing the Non-Gaussian Surface in Sum of Gaussian Surfaces

et al. 2012

AMR

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The decomposition of the multivariate Non-Gaussian PDF in the sum of a Gaussian PDF instead of the Gram-Charlier series is investigated. Four parameters need to be found by minimizing the integrated square of the difference between Cox-Munk function and its approximation. The backscattering radar cross section (RCS) of the surface is calculated by the Kirchhoff approximation (KA) under different value of k using the formula of decomposition of the Non-Gaussian. The condition of KA satisfying electromagnetic scattering scale from Gaussian and Non-Gaussian surfaces is taken into account by computing the backscattering coefficients in HH and VV polarity.

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Section: Introductionmentioning

confidence: 99%

Decomposing the Non-Gaussian Surface in Sum of Gaussian Surfaces

et al. 2012

AMR

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Numerical Computation of the Electromagnetic Bias in GNSS-R Altimetry

Ghavidel

Schiavulli

Camps

2016

IEEE Trans. Geosci. Remote Sensing

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In radar altimetry the electromagnetic (EM) bias is originated by the smaller reflectivity of wave crests than troughs, thus the average sea surface height is under-estimated. Bias uncertainty is currently the largest factor in altimetry error budgets. The EM bias in a bistatic forward-scattering configuration at L-band, such as in Global Navigation Satellite SystemsReflectometry (GNSS-R) altimetry, remains one of the major sources of uncertainty in the altimetry error budget. In this work the EM bias is computed using numerical simulations.To do so, a time-dependent synthetic non-Gaussian sea surface is created using the PiersonMoskowitz and Elfouhaily sea surface height spectra and spreading function. The sea surface is then discretized in facets and "illuminated" using a Right Hand Circular Polarization data at C-and Ku-bands. Then, the numerical model is applied at L-band, for bistatic configurations, including different azimuth angles, and different wind speeds. It is found that the EM bias is almost insensitive to the sea surface spectra selected and increases with increasing wind speed and incidence/scattering angle (up to ~20 cm at θi,s = 45° and U10 = 12 m/s), and it also exhibits a non-negligible azimuthal dependence, that must be accounted for in the error budgets of upcoming GNSS-R altimetry missions.

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