Electromagnetic Scattering Research Articles

An Operator Preconditioned Combined Field Integral Equation for Electromagnetic Scattering

An Operator Preconditioned Combined Field Integral Equation for Electromagnetic Scattering

Research on Radar Target Detection Based on the Electromagnetic Scattering Imaging Algorithm and the YOLO Network

In this paper, the radar imaging technology based on the time-domain (TD) electromagnetic scattering algorithm is used to generate image datasets quickly and apply them to target detection research. Considering that radar images are different from optical images, this paper proposes an improved strategy for the traditional You Only Look Once (YOLO)v3 network to improve target detection accuracy on radar images. The speckle noise in radar images can cover the real information of a target image and increase the difficulty of target detection. The attention mechanisms are added to the traditional YOLOv3 network to strengthen the weight of the target region. By comparing the target detection accuracy under different attention mechanisms, an attention module with higher detection accuracy is obtained. The validity of the proposed detection network is verified on a simulation dataset, a measured real dataset, and a mixed dataset. This paper is about an interdisciplinary study of computational electromagnetics, remote sensing, and artificial intelligence. Experiments verify that the proposed composite network has better detection performance.

Modes, bounds, and synthesis of optimal electromagnetic scatterers

Abstract This paper presents an optimal synthesis of material distributions in obstacles for maximal extinction, scattering, or absorption. The material synthesis is based on an explicit construction utilizing the current distribution derived from physical bounds excited from the far-field. The bounds are expressed in radiation modes for materials restricted by their resistivity and characteristic modes for materials restricted by the contrast. The results are valid for arbitrary shapes, and analytical expressions are provided for spherical shapes.

Efficient Electromagnetic Scattering Signature Restoration for UAV Swarm Targets Based on Equivalent Principle Algorithm and Empirical Interpolation Method

Efficient Electromagnetic Scattering Signature Restoration for UAV Swarm Targets Based on Equivalent Principle Algorithm and Empirical Interpolation Method

Multifunctional Metamaterial with Reconfigurable Electromagnetic Scattering Properties for Advanced Stealth and Adaptive Applications.

The rapid development of radar detection systems has led to an increased sensitivity to the electromagnetic (EM) scattering properties of detected targets. Flexible and adaptable EM scattering properties significantly enhance the survivability of battlefield weapons. This paper presents the design of a novel multifunctional metamaterial with reconfigurable EM scattering properties based on a bistable curved beam. In addition to the cushioning and energy absorption properties of curved beams, the metamaterial achieves more than 90% EM absorption in the frequency range of 2.17-17.31GHz, with a relative thickness of only 0.09λL. The bistable nature of the metamaterial allows it to switch between different states. Moreover, combined with the digital coding, this metamaterial can continuously adjust the absorbing bandwidth and further enhance the EM absorption rate within a specific frequency band range. If applied to satellite configurations, the developed metamaterial significantly reduces the radar cross section and offers potential applications in reconfiguring EM scattering properties, when applied to satellite configurations. By actively controller and reconstructing the EM scattering properties at certain frequency points, the metamaterial can achieve camouflage, providing innovative solutions for future stealth technology, electronic countermeasures, and deception jamming in radar detection.

A Synthetic Aperture Radar Imaging Simulation Method for Sea Surface Scenes Combined with Electromagnetic Scattering Characteristics

Synthetic aperture radar (SAR) simulation is a vital tool for planning SAR missions, interpreting SAR images, and extracting valuable information. SAR imaging is essential for analyzing sea scenes, and the accuracy of sea surface and scattering models is crucial for effective SAR simulations. Traditional methods typically employ empirical formulas to fit sea surface scattering, which are not closely aligned with the principles of electromagnetic scattering. This paper introduces a novel approach by constructing multiple sea surface models based on the Pierson–Moskowitz (P-M) sea spectrum, integrated with the stereo wave observation projection (SWOP) expansion function to thoroughly account for the influence of wave fluctuation characteristics on radar scattering. Utilizing the shooting and bouncing ray-physical optics (SBR-PO) method, which adheres to the principles of electromagnetic scattering, this study not only analyzes sea surface scattering characteristics under various sea conditions but also facilitates the computation of scattering coupling between multiple targets. By constructing detailed scattering distribution data, the method achieves high-precision SAR simulation results. The scattering model developed using the SBR-PO method provides a more nuanced description of sea surface scenes compared to traditional methods, achieving an optimal balance between efficiency and accuracy, thus significantly enhancing sea surface SAR imaging simulations.

Physics-aware neural network-based parametric model-order reduction of the electromagnetic analysis for a coated component

AbstractFinite element (FE) analysis is one of the most accurate methods for predicting electromagnetic field scatter; however, it presents a significant computational overhead. In this study, we propose a data-driven parametric model-order reduction (pMOR) framework to predict the scattered electromagnetic field of FE analysis. The surface impedance of a coated component is selected as parameter of analysis. A physics-aware (PA) neural network incorporated within a least-squares hierarchical-variational autoencoder (LSH-VAE) is selected for the data-driven pMOR method. The proposed PA-LSH-VAE framework directly accesses the scattered electromagnetic field represented by a large number of degrees of freedom (DOFs). Furthermore, it captures the behavior along with the variation of the complex-valued multi-parameters. A parallel computing approach is used to generate the training data efficiently. The PA-LSH-VAE framework is designed to handle over 2 million DOFs, providing satisfactory accuracy and exhibiting a second-order speed-up factor.

Electromagnetic Scattering Properties and Characterisation of Sintered SiC Composite–Based Microwave Spectrum

واحدة من أكثر مواد السيراميك الهيكلية الواعدة هي كربيد السيليكون(SiC) ، حيث له خصائص حرارية وكهروميكانيكية ممتازة. هذه الخصائص مفيدة ل CMC لتعزيز أداء المركب خاصة عند إضافات النانو المتكاملة. في هذا البحث, تم تصنيع مركب SiC من SiC بثلاثة تركيزات مع ZnO و Si. تم اختبار الخواص المغناطيسية لجميع المخاليط باستخدام مراقبة العينة الاهتزازية (VSM). تم تلبيد العينات الخضراء في فرن التلبيد عند 1600 درجة مئوية في بيئة النيتروجين. تم اختبار جميع المركبات التي تم الحصول عليها وتوصيفها باستخدام تقنيات و توصيفات مختلفة مثل حيود الأشعة السينية، ومورفولوجيا السطح تمت باستخدام FESEM، ومحلل الشبكة لاختبار الخصائص العازلة للعينات. بناء على بيئة التلبيد، تم اكتشاف نيتريد السيليكون في المركب بسبب عملية النتردة على طول المركب. من ناحية أخرى، تم حساب الخصائص المغناطيسية والامتصاصية لجميع مركبات SiC. تعتبر الخصائص العازلة عالية حيث يميل المركب إلى أن يكون عاكسا في نطاق التردد المنخفض و نافذ كلما زاد التردد على طول نطاق التردد.

Manufactured solutions for an electromagnetic slot model

The accurate modeling of electromagnetic penetration is an important topic in computational electromagnetics. Electromagnetic penetration occurs through intentional or inadvertent openings in an otherwise closed electromagnetic scatterer, which prevent the contents from being fully shielded from external fields. To efficiently model electromagnetic penetration, aperture or slot models can be used with surface integral equations to solve Maxwell's equations. A necessary step towards establishing the credibility of these models is to assess the correctness of the implementation of the underlying numerical methods through code verification. Surface integral equations and slot models yield multiple interacting sources of numerical error and other challenges, which render traditional code-verification approaches ineffective. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources for the method-of-moments implementation of the electric-field integral equation with a slot model. We demonstrate the effectiveness of these approaches for a variety of cases.

2-D Electromagnetic Scattering From Multiple Arbitrarily Anisotropic Inhomogeneities Embedded in Multilayered Biaxially Anisotropic Elliptical Cylinders Solved by the Hybrid SIM/SEM

2-D Electromagnetic Scattering From Multiple Arbitrarily Anisotropic Inhomogeneities Embedded in Multilayered Biaxially Anisotropic Elliptical Cylinders Solved by the Hybrid SIM/SEM

An Adaptive Frequency Sampling Technique Based on SMoM and EDM for Wideband Electromagnetic Scattering Data of Multiscale Targets

An Adaptive Frequency Sampling Technique Based on SMoM and EDM for Wideband Electromagnetic Scattering Data of Multiscale Targets

Combination of Methods of Volume and Surface Integral Equations in Problems of Electromagnetic Scattering by Small Thickness Structures

Combination of Methods of Volume and Surface Integral Equations in Problems of Electromagnetic Scattering by Small Thickness Structures

2-D Electromagnetic Scattering and Inverse Scattering From Anisotropic Objects Under TE Illumination Solved by the Hybrid SIM/SEM

2-D Electromagnetic Scattering and Inverse Scattering From Anisotropic Objects Under TE Illumination Solved by the Hybrid SIM/SEM

Stochastic Electromagnetic Scattering From Stratified Media of Inhomogeneous Layers With Random Constitutive Parameters

Stochastic Electromagnetic Scattering From Stratified Media of Inhomogeneous Layers With Random Constitutive Parameters

On the Efficient Electromagnetic Scattering Analysis From Targets With Electrically Small Surface Discontinuities

On the Efficient Electromagnetic Scattering Analysis From Targets With Electrically Small Surface Discontinuities

An IGFBM-SAA Fast Algorithm for Solving Electromagnetic Scattering from Layered Media Rough Surfaces

This article proposes a new fast solution algorithm (IGFBM-SAA), which combines the Improved Generalized Forward and Backward Method (IGFBM) with Spectral Acceleration Approach (SAA), which can effectively solve the electromagnetic scattering problem of layered rough surface. In this article, the electric field integral equations (EFIE) for layered rough surfaces is established, and the traditional forward and backward method (FBM) is introduced. Then, based on the traditional FBM algorithm, an Improved Generalized Forward and Backward Method is proposed and, by using the SAA technique in its iterative process, the computation of matrix-vector multiplication is accelerated, thus enabling rapid solution. In the algorithm validation, the same rough surface was calculated using the MoM, FBM, and IGFBM-SAA. The study found that when root mean square (RMS) heights are h1=h2=0.1λ, the convergence accuracy can reach τ=10−7 after 14 iterations. However, as the roughness increases to h1=h2=0.3λ and h1=h2=0.5λ, the convergence accuracy falling to τ=10−5 and τ=10−5, respectively. This indicates that it is necessary to adjust the integration parameters to improve the convergence accuracy. In addition, it was found that when the size of the rough surface is 25.6λ, the computational times for calculations are 91 s (IGFBM-SAA), 197 s (FBM), and 410 s (MoM), respectively. When the size of the rough surface increases to 51.2λ, the computational time differences become more significant, with 236 s, 756 s, and 2547 s being the respective values. This indicates that the proposed algorithm in this article has significant computational speed advantages when dealing with larger rough surfaces. Based on this algorithm, this article studied the electromagnetic scattering characteristics of layered rough surfaces with different parameters (RMS height, dielectric constant, and correlation length), and relevant research results can provide valuable references for areas such as radar target recognition and radar stealth technology, thereby enhancing the accuracy and reliability of radar detection as well as radar stealthperformance.

Physics-informed Deep Learning to Solve 2D Electromagnetic Scattering Problems

The utilization of physics-informed deep learning (PI-DL) methodologies provides an approach to augment the predictive capabilities of deep learning (DL) models by constraining them with known physical principles. We utilize a PI-DL model called the deep operator network (DeepONet) to solve two-dimensional (2D) electromagnetic (EM) scattering problems. Numerical results demonstrate that the discrepancy between the DeepONet and conventional method of moments (MoM) is small, while maintaining computational efficiency.

A Physics-Induced Deep Learning Scheme for Electromagnetic Inverse Scattering

A Physics-Induced Deep Learning Scheme for Electromagnetic Inverse Scattering

Fast Direct Solution of Electromagnetic Scattering From Metallic Objects in a Planarly Layered Medium

Fast Direct Solution of Electromagnetic Scattering From Metallic Objects in a Planarly Layered Medium

Analysis on Aperture Size for Electromagnetic Scattering by Circular Strips with Impedance Boundary Conditions

Analysis on Aperture Size for Electromagnetic Scattering by Circular Strips with Impedance Boundary Conditions