One-dimensional fractal model of the sea surface

Berizzi, F.; Mese, E. Dalle; Pinelli, G.

doi:10.1049/ip-rsn:19990259

Cited by 40 publications

(16 citation statements)

References 6 publications

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“…So, the model is realistic as also confirmed by the analysis performed in [10] and in [11]. The scattering coefficient, which in turn is proportional to the EM scattered signal, is calculated under Kirchhoff approximation and its expression is [1] (2) with (3) where ,…”

Section: Sea Fractal Model and Scattering Coefficient Expressionmentioning

confidence: 68%

“…This model was validated in two different ways 1) by numerically demonstrating [11] the statistical distribution of EM sea scattered signal agrees the typical Rayleigh, Weibull, and Lognormal distributions found in literature from the analysis of real data [12] and 2) by evaluating a closed form expression of the directional and the omnidirectional sea wave spectra and by comparing the result with the most common models of Pierson Moskowitz and Jonswap and with real data. The results show that the "fractal spectrum" is able to fit the other models and shows the better performance in term of the minimum mean square error when compared with real spectra measured by ondametric buoys in the Mediterranean sea [10].…”

Section: Introductionmentioning

confidence: 74%

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Scattering from a 2D sea fractal surface: fractal analysis of the scattered signal

Berizzi

Dalle-Mese

2002

IEEE Trans. Antennas Propagat.

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This paper is the second part of the work presented in the June Issue of the IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. We analytically demonstrate that the electromagnetic (EM) sea scattered signal retains certain fractal properties of the sea surface. Starting from the expression of the scattering coefficient derived in the first part of the work, we theoretically show that the fractal dimension of the in phase and quadrature components of the EM signal scattered from a sea fractal surface is linearly related to the fractal dimension of the sea surface. This result holds under the hypothesis of Kirchhoff approximation. Bearing in mind that the sea fractal dimension gives a measure of the irregularity degree of the surface, we can exploit this result to make a remote estimation of the roughness surface through the fractal analysis of the scattered signal. This is a very interesting result and it could be successfully used in remote sensing applications for classification, target detection, sea surface traffic monitoring, sea current analysis, oil slick and ship wakes recognition, pollution analysis, etc.

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Section: Sea Fractal Model and Scattering Coefficient Expressionmentioning

confidence: 68%

Section: Introductionmentioning

confidence: 74%

Scattering from a 2D sea fractal surface: fractal analysis of the scattered signal

Berizzi

Dalle-Mese

2002

IEEE Trans. Antennas Propagat.

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“…1.The angle of incidence of the EM wave is θ i with respect to the vertical z axis, where the incident and scattered wave vectors are denoted by k i and k s respectively [1].. Following [1], and in order to describe the surface roughness, a one-dimensional fractal function is used [1], [3], [4]. This fractal function is described by the following equation:…”

Section: Problem Geometry and Mathematical Formulationmentioning

confidence: 99%

Characterization of 2D and 3D Rough Fractal Surfaces from Backscattered Radar Data

Kotopoulis

Pouraimis

Kallitsis

et al. 2017

International Conference KNOWLEDGE-BASED ORGANIZATION

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“…However, for small slope and deep sea situation, the nonlinear components can be neglected [6]. In this case, the sea surface model may be denoted by a linear combination of sinusoidal functions [7] and can be expressed as…”

Section: Fractal Model Of Rough Sea Surfacementioning

confidence: 99%

Estimation and analysis of lacunarity of scattering signals at different incident angles

Tao

2010

IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS

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The sea surface has the fractal nature. For normal incidence, some methods have been developed for extracting fractal parameters from the electromagnetic (EM) scattered signals. When the EM waves of different incident angles are scattered by the fractal sea surface, the scattered signal recorded at observation point will show many different properties, which will affect the accuracy of estimation of fractal parameters. In this paper, based on the method of skeleton of wavelet transform modulus maxima (WTMM), we analyze the hierarchical structures of the EM scattered signals at different incident angles to estimate the lacunarity of the fractal surface. It is shown that the optimal incident angle is between the sea surface and incident pulse passing through the mirror position of observation point and the midpoint of one-dimensional sea surface, approximately. The results of simulation are found interestingly successful to use the estimated parameters in remote sensing applications.

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One-dimensional fractal model of the sea surface

Cited by 40 publications

References 6 publications

Scattering from a 2D sea fractal surface: fractal analysis of the scattered signal

Scattering from a 2D sea fractal surface: fractal analysis of the scattered signal

Characterization of 2D and 3D Rough Fractal Surfaces from Backscattered Radar Data

Estimation and analysis of lacunarity of scattering signals at different incident angles

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