A Domain Decomposition Finite-Element Method for Modeling Electromagnetic Scattering From Rough Sea Surfaces With Emphasis on Near-Forward Scattering

Özgün, Özlem; Kuzuoğlu, Mustafa

doi:10.1109/tap.2018.2874766

Cited by 15 publications

(5 citation statements)

References 40 publications

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“…Differential methods generally require boundary conditions to truncate open spaces and can theoretically handle various shapes and parameterized media situations. Ozgun and Kantartzis (2019) presented a high-fidelity full-wave simulator for solving the problem of 2D electromagnetic scattering over a 1D sea surface [11]. Ohtani et al (2021) applied the nonstandard finite-difference time-domain (NS-FDTD) technique to assess the overall RCS evaluation of various aircraft configurations with an electrically large size [12].…”

Section: Introductionmentioning

confidence: 99%

A Novel Radar Cross-Section Calculation Method Based on the Combination of the Spectral Element Method and the Integral Method

Zhao,

Chen,

Zhuang

et al. 2024

Symmetry

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This article proposes a novel method for calculating radar cross-sections (RCSs) that combines the spectral element method and the integral method, allowing for RCS calculations at any position in a free space or a half-space. This approach replaces the field source with an incident field using the scattered field equation of the spectral element method, enabling the arbitrary placement of the field source without being limited by the computational domain. By applying the superposition theorem and the volume equivalence principle, the scattered field of the objects at any position is obtained through integral equations, eliminating limitations on the computation points imposed by the computational domain. Based on Green’s function’s important role throughout the calculation process and its symmetry properties, the RCS calculation of symmetric models will be more advantageous. Finally, several examples, including symmetry models, are provided to validate both the feasibility and accuracy of this proposed method.

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Section: Introductionmentioning

confidence: 99%

A Novel Radar Cross-Section Calculation Method Based on the Combination of the Spectral Element Method and the Integral Method

Zhao,

Chen,

Zhuang

et al. 2024

Symmetry

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“…Approximate method includes: Kirchhoff Approximation Method [7,8], Phase Perturbation Method, Small Perturbation Method, Small Slop Approximation, and Physical Optical Method [9][10][11] , etc. Approximation method is simple to model, fast to calculate and less computation consume, but their calculation results are often not accurate enough, now people are paying more and more attention on the numerical method such as the MOM method, fast multilevel method, finite element method, FDTD and forward-backward method [12][13][14][15] ,etc. The numerical method is less efficient than approximate method in terms of calculation, but its calculation accuracy is higher，and the obtained result is more universal.…”

Section: Introductionmentioning

confidence: 99%

Composite Scattering Computation from Multiple Dielectric Targets of One-Dimensional Fractal Sea Surface Using MOM

Wang,

Wang

2023

Preprint

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Bistatic scattering coefficient have important application of ocean active microwave remote sensing. In this paper, a general expression of the composite scattering coefficient for multiple dielectric targets of one-dimensional fractal sea surface is derived by MOM method. Secondly, the bistatic scattering coefficient is computed, there are two class missile targets and one class ship target of one-dimensional fractal sea surface, and the influence of the water dielectric constant, fractal dimension, wind speed, the target dielectric constant and spatial position is discussed, and the corresponding conclusions are given. The proposed algorithm is able to solve some composite scattering problems, such as “dielectric or conductive object + rough surface”, “dielectric or conductive floating object +rough ”and it has certain generalization and reference.

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“…2022, 14, 4657 2 of 17 be divided into two main kinds: the low-frequency rigorous numerical methods and the high frequency approximate methods. The low-frequency rigorous numerical methods are based on the numerical solution of various EM field differential and integral equations, such as the Method of Moments (MoM) [2,3], Finite-Difference Time-Domain (FDTD) [4][5][6], Finite Elements Method (FEM) [7], etc. They have high computational accuracy but have low computational efficiency when dealing with large-scale scattering problems.…”

Section: Introductionmentioning

confidence: 99%

3D Sea Surface Electromagnetic Scattering Prediction Model Based on IPSO-SVR

et al. 2022

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An Improved Particle Swarm Optimization Algorithm-Support Vector Regression Machine (IPSO-SVR) prediction model is developed in this paper to predict the electromagnetic (EM) scattering coefficients of the three-dimensional (3D) sea surface for large scenes in real-time. At first, the EM scattering model of the 3D sea surface is established based on the Semi-Deterministic Facet Scattering Model (SDFSM), and the validity of SDFSM is verified by comparing with the measured data. Using the SDFSM, the data set of backscattering coefficients from 3D sea surface is generated for different polarizations as the training samples. Secondly, an improved particle swarm optimization algorithm is proposed by combining the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The combined algorithm is utilized to optimize the parameters and train the SVR to build a regression prediction model. In the end, the extrapolated prediction for backscattering coefficients of the 3D sea surface is performed. The Root Mean Square Error (RMSE) of the IPSO-SVR-based prediction model is less than 1.2 dB, and the correlation coefficients are higher than 91%. And the prediction accuracy of the PSO-SVR-based, GA-SVR-based and IPSO-SVR-based prediction models is compared. The average RMSE of the PSO-SVR-based and GA-SVR-based prediction models is 1.4241 dB and 1.6289 dB, respectively. While the average RMSE of the IPSO-SVR-based prediction model is reduced to 1.1006 dB. Besides, the average correlation coefficient of the PSO-SVR-based and GA-SVR-based prediction models is 94.36% and 93.93%, respectively. While the average correlation coefficient of the IPSO-SVR-based prediction model reached 95.12%. It demonstrated that the IPSO-SVR-based prediction model can effectively improve the prediction accuracy compared with the PSO-SVR-based and GA-SVR-based prediction models. Moreover, the simulation time of IPSO-SVR-based prediction model is significantly decreased compared with the SDFSM, and the speedup ratio is greater than 15.0. Therefore, the prediction model in this paper has practical application in the real-time computation of sea surface scattering coefficients in large scenes.

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A Domain Decomposition Finite-Element Method for Modeling Electromagnetic Scattering From Rough Sea Surfaces With Emphasis on Near-Forward Scattering

Cited by 15 publications

References 40 publications

A Novel Radar Cross-Section Calculation Method Based on the Combination of the Spectral Element Method and the Integral Method

A Novel Radar Cross-Section Calculation Method Based on the Combination of the Spectral Element Method and the Integral Method

Composite Scattering Computation from Multiple Dielectric Targets of One-Dimensional Fractal Sea Surface Using MOM

3D Sea Surface Electromagnetic Scattering Prediction Model Based on IPSO-SVR

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