Implementation and validation of the curvilinear coordinate method for the scattering of electromagnetic waves from two-dimensional dielectric random rough surfaces

Dusséaux, Richard; Braham, K. Aät; Granet, G.

doi:10.1080/17455030802126913

Cited by 3 publications

(16 citation statements)

References 21 publications

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“…The method was investigated in near and far field zones by means of convergence tests on the scattering amplitudes and the power balance criterion. The theory was verified by comparisons with published numerical and experimental data [5][6][7]. We showed that the MonteCarlo simulations based on the C-method have been successful in predicting backscattering enhancement and in analyzing very rough surfaces.…”

Section: Introductionsupporting

confidence: 48%

“…The surface separates the vacuum from a material with a complex relative permittivity. The incident wave vector k 0 is defined from the zenith angle θ 0 and the azimuth angle ϕ 0 [6,7]. In horizontal polarization (a = h), the electric field vector is parallel to the Oxy plane.…”

Section: Formulation Of Problemmentioning

confidence: 99%

“…The scattered field can be obtained by using the C-method [1][2][3][4][5][6][7] and the translation coordinate system defined by:…”

Section: Coordinate System -Covariant Components Of Fieldmentioning

confidence: 99%

“…The boundary value problem allows the scattering amplitudes to be determined. The C-method is an efficient theoretical tool for analyzing grating diffraction [1][2][3] and rough surfaces [4][5][6][7]. The method was investigated in near and far field zones by means of convergence tests on the scattering amplitudes and the power balance criterion.…”

Section: Introductionmentioning

confidence: 99%

“…The backscattering coefficient is estimated by averaging the scattering amplitudes over several realizations. For each realization, the scattering amplitudes are obtained by the curvilinear coordinate method, commonly called the Cmethod [1][2][3][4][5][6][7]. This method is based on Maxwell's equations under their tensorial form written in a nonorthogonal coordinate system where the boundary surfaces coincide with coordinate surfaces.…”

Section: Introductionmentioning

confidence: 99%

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Study of Backscatter Signature for Seedbed Surface Evolution Under Rainfall --- Influence of Radar Precision

Dusséaux¹,

Vannier²,

Taconet³

et al. 2012

PIER

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Abstract-We propose a 3D-approach of the soil surface height variations, either for the roughness characterization by the mean of the bidimensional correlation function, or as input of a backscattering model. We consider plots of 50 cm by 50 cm and two states of roughness of seedbed surfaces: an initial state just after tillage and a second state corresponding to the soil roughness evolution under a rainfall event. We show from stereovision data that the studied surfaces can be modelled as isotropic Gaussian processes. We study the change of roughness parameters between the two states. To discuss the relevance of their differences, we find from Monte-Carlo simulations the bias and variance of estimator for each roughness parameters. We study the roughness and moisture combined influences upon the direct backscattering coefficients by means of an exact method based on Maxwell's equations written in a nonorthogonal coordinate system and by averaging the scattering amplitudes over several realizations. We discuss results taking into account the numerical errors and the precision of radar. We show that the ability of the radar to discriminate the different states of seedbed surfaces is clearly linked to its precision.

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Section: Introductionsupporting

confidence: 48%

Section: Formulation Of Problemmentioning

confidence: 99%

“…The scattered field can be obtained by using the C-method [1][2][3][4][5][6][7] and the translation coordinate system defined by:…”

Section: Coordinate System -Covariant Components Of Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Study of Backscatter Signature for Seedbed Surface Evolution Under Rainfall --- Influence of Radar Precision

Dusséaux¹,

Vannier²,

Taconet³

et al. 2012

PIER

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A Complex Mix-Shifted Parallel Qr Algorithm for the C-Method

Pan¹,

Dusséaux²,

Emad³

2016

PIER B

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The C-method is an exact method for analyzing gratings and rough surfaces. This method leads to large-size dense complex non-Hermitian eigenvalue. In this paper, we introduce a parallel QR algorithm that is specifically designed for the C-method. We define the "early shift" for the matrix according to the observed properties. We propose a combination of the "early shift", Wilkinson's shift and exceptional shift together to accelerate convergence. First, we use the "early shift" in order to have quick deflation of some eigenvalues. The multi-window bulge chain chasing and parallel aggressive early deflation are used. This approach ensures that most computations are performed in level 3 BLAS operations. The aggressive early deflation approach can detect deflation much quicker and accelerate convergence. Mixed MPI-Open MP techniques are used for performing the codes to hybrid shared and distributed memory platforms. We validate our approach by comparison with experimental data for scattering patterns of two-dimensional rough surfaces.

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Statistical Characterization of Bare Soil Surface Microrelief

Vannier¹,

Taconet²,

Dusséaux³

et al. 2014

Advanced Geoscience Remote Sensing

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Because the soil surface occurs at the boundary between the atmosphere and the pedosphere, it plays an important role for geomorphologic processes. Roughness of soil surface is a key parameter to understand soil properties and physical processes related to substrate movement, water infiltration or runoff, and soil erosion. It has been noted by many authors that most of the soil surface and water interaction processes have characteristic lengths in millimeter scales. Soil irregularities at small scale, such as aggregates, clods and interrill depressions, influence water outflow and infiltration rate. They undergo rapid changes caused by farming imple‐ ments, followed by a slow evolution due to rainfall events. Another objective of soil surface roughness study is investigating the effects of different tillage implements on soil physical properties (friability, compaction, fragmentation and water content) to obtain an optimal crop emergence. Seedbed preparation focuses on the creation of fine aggregates and the size distribution of aggregates and clods produced by tillage operations is frequently measured. Active microwave remote sensing allows potential monitoring of soil surface roughness or moisture retrieving at field scale using space-based Synthetic Aperture Radars (SAR) with high spatial resolution (metric or decametric). The scattering of microwaves depends on several surface characteristics as well as on imagery configuration. The SAR signal is very sensitive to soil surface irregularities and structures (clod arrangement, furrows) and moisture content in the first few centimeters of soil (depending on the radar wavelength). In order to link the remote sensing observations to scattering physical models as well as for modelling purpose, key features of the soil microtopography should be characterized. However, this characteri‐ zation is not fully understood and some dispersion of roughness parameters can be observed in the same field according to the methodology used. It seems also, that when describing surface roughness as a whole, some information related to structured elements of the micro‐ topography is lost

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Implementation and validation of the curvilinear coordinate method for the scattering of electromagnetic waves from two-dimensional dielectric random rough surfaces

Cited by 3 publications

References 21 publications

Study of Backscatter Signature for Seedbed Surface Evolution Under Rainfall --- Influence of Radar Precision

Study of Backscatter Signature for Seedbed Surface Evolution Under Rainfall --- Influence of Radar Precision

A Complex Mix-Shifted Parallel Qr Algorithm for the C-Method

Statistical Characterization of Bare Soil Surface Microrelief

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