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Numerical and Analytical Methods for Complex Electromagnetic Media 复杂电磁介质的数值与解析方法
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3600937
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引用次数: 0
Microwave, mm and THz Imaging and Sensing Systems and Technologies for Medical Applications 微波,毫米和太赫兹成像和传感系统和技术的医疗应用
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3600935
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引用次数: 0
IEEE Transactions on Antennas and Propagation Information for Authors IEEE天线与传播信息学报
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3600941
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引用次数: 0
Erratum to “Dual-Band High-Gain Omnidirectional Slender Dipole Array With Small Cross Section for WLAN Application” “用于WLAN应用的双波段高增益全向小截面细长偶极子阵列”的勘误表
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3606293
Dan Liu;Le Chang;Yue Li;Yongjian Zhang;Yuehua Sun;Anxue Zhang
In the above article [1], the sentences in introduction were written as “The second method uses multiple omnidirectional antennas [19], [20], [21], [22], among which the antenna in [20] is more typical, where a dual-band horizontally-polarized (HP) omnidirectional antenna based on a normal loop and an Alford loop achieves a cross diameter of $0.3lambda _{mathrm {L}}$ and a gain range of –0.6 to –1.3 dBi. However, this method can only produce a gain range of –2 to –1.3 dBi, which does not meet the gain requirements of modern routers.”
在上述文章[1]中,引言部分的表述为“第二种方法使用多个全向天线[19],[20],[21],[22],其中[20]中的天线更为典型,其中基于法向环和Alford环的双频水平极化(HP)全向天线的交叉直径为$0.3lambda _{mathrm {L}}$,增益范围为-0.6 ~ -1.3 dBi。”但是,这种方法只能产生-2 ~ -1.3 dBi的增益范围,不能满足现代路由器的增益要求。”
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引用次数: 0
IEEE Transactions on Antennas and Propagation Publication Information IEEE天线与传播学报出版信息
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3600933
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引用次数: 0
Recent Advances in Synthetic Aperture Antennas: Design, Modelling, and Measurement 合成孔径天线的最新进展:设计、建模和测量
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3600939
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引用次数: 0
Editorial Special Article Collection on Antennas and Propagation for Space Applications 面向空间应用的天线与传播编辑专题文集
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3597125
Nelson J. G. Fonseca;Oscar Quevedo-Teruel;Goutam Chattopadhyay
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引用次数: 0
Polarization and Pattern Agile Planar Periodic 2-D Bull’s-Eye Leaky Wave Antenna With Open-Stopband Suppression 偏振和方向灵活的开阻带抑制平面周期二维牛眼漏波天线
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-10 DOI: 10.1109/TAP.2025.3605055
Sadia Riaz;Davide Comite;Paolo Baccarelli;Symon K. Podilchak
A radially periodic 2-D leaky wave antenna (LWA) with high gain at broadside, reduced sidelobes, and suppressed open-stopband (OSB) is presented in this communication. The antenna is low profile and is defined by a printed, double microstrip bull’s-eye aperture. To support polarization and pattern agility, as well as applications in full-duplex systems and dual-polarization scenarios, the antenna is fed with a compact multislot array at the center of LWA, enabled by substrate integrated waveguide (SIW) technology. When considering differential excitation, the simulations and measurements demonstrate a maximum realized gain of more than 17 dBi at broadside at about 18.4 GHz. Furthermore, due to the suppression of the OSB, persistent broadside radiation is supported from 18 to 19 GHz, along with continuous and sustained directive radiation when the main beam scans through broadside, which is in agreement with leaky-wave (LW) theory. Applications include vehicle antennas and V2X communication systems, satellite connectivity, polarization and pattern diversity scenarios, radar and monopulse systems, as well as 5G/6G wireless communications.
在这种通信中,提出了一种具有高宽边增益、减少旁瓣和抑制开阻带(OSB)的径向周期二维漏波天线(LWA)。天线是低轮廓和定义的印刷,双微带牛眼孔径。为了支持极化和模式敏捷性,以及在全双工系统和双极化场景中的应用,该天线在LWA中心采用紧凑的多槽阵列馈电,并通过衬底集成波导(SIW)技术实现。当考虑差分激励时,仿真和测量表明,在约18.4 GHz时,最大实现增益大于17 dBi。此外,由于抑制了OSB,在18 ~ 19 GHz范围内支持持续的宽侧辐射,并且在主波束扫描宽侧时支持连续和持续的定向辐射,这与漏波(LW)理论一致。应用包括车载天线和V2X通信系统、卫星连接、极化和模式分集场景、雷达和单脉冲系统,以及5G/6G无线通信。
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引用次数: 0
Omnidirectional Absorber for Dual Polarizations Based on Generalized Brewster Effect in Highly Dissipative Metasurface 基于高耗散超表面广义布鲁斯特效应的双极化全向吸收体
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-09 DOI: 10.1109/TAP.2025.3604957
Jingxin Tang;Chenyu Wang;Liang Peng;Yaqing Huang;Xiaojun Hu;Zhiyu Wang;Bo Yang;Naoki Shinohara;Dexin Ye
Brewster effect originally refers to the reflectionless transmission of a TM-polarized wave impinging on a lossless dielectric surface at a particular angle. It is generally thought that either the introduction of loss or the change of polarization will break the reflectionless phenomenon. Here, we derive an analytical solution for achieving the generalized Brewster effect in highly dissipative anisotropic media for both TE- and TM-polarized waves. Based on the composite electric and magnetic resonator, we designed a 3-D metasurface with controllable Brewster angles to absorb dual-polarized incident waves without reflection. By stacking massive different metasurface units, each with a deliberately designed Brewster angle, it is possible to achieve omnidirectionally matched absorption for dual-polarized incident waves from a given source. As a proof of concept, we implemented an inhomogeneous planar metasurface. Each unit of this metasurface has a Brewster angle precisely adjusted according to a given line source, which is used to absorb the corresponding impinging wave without reflection. Both full-wave simulations and experimental measurements confirm the nearly omnidirectionally matched absorption. Our work offers a promising approach for applications of metasurfaces in electromagnetic shielding, compatibility, and microwave measurements.
布鲁斯特效应最初是指tm偏振波以一定角度撞击在无损介质表面上的无反射传输。一般认为,要么引入损耗,要么改变偏振,就会打破无反射现象。在这里,我们推导了在高耗散各向异性介质中实现TE和tm极化波的广义布鲁斯特效应的解析解。基于复合谐振腔,设计了具有可控布鲁斯特角的三维超表面,实现了对双极化入射波的无反射吸收。通过堆叠大量不同的超表面单元,每个单元都有一个精心设计的布鲁斯特角,可以实现来自给定源的双偏振入射波的全方位匹配吸收。作为概念验证,我们实现了一个非均匀平面超表面。该超表面的每个单元都有一个根据给定线源精确调整的布鲁斯特角,用于吸收相应的冲击波而不反射。全波模拟和实验测量都证实了几乎全方向匹配的吸收。我们的工作为超表面在电磁屏蔽、兼容性和微波测量中的应用提供了一种有前途的方法。
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引用次数: 0
DeepDPO: A Self-Supervised Deep Learning Approach Based on the Differentiable Physical Optics Method for 3-D Reconstruction of Perfect Electric Conductors 一种基于可微物理光学方法的自监督深度学习方法用于完美电导体的三维重建
IF 5.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-09-05 DOI: 10.1109/TAP.2025.3604072
Lizhen Yang;Si Zuo;Yuxuan Li;Yuhao Shen;Peng Zhang;Hai Lin
This communication presents a novel deep learning (DL) framework for solving 3-D inverse-scattering problems (ISPs), aimed at reconstructing geometric shapes of perfect electric conductors (PECs) from scattered electric fields. ISPs are inherently ill-posed and nonlinear, challenging both conventional and DL methods. To address this, we propose DeepDPO, a self-supervised DL approach that integrates the reliability of conventional model-based methods with the efficiency of learning-based approaches. The framework employs a probabilistic auto-decoder neural network (PADNN) for continuous geometric representation using a signed distance field (SDF) and incorporates the mesh-based physical optics (PO) method for forward scattering calculations. The reconstructed model is obtained by decoding the object-specific code through the PADNN and optimizing it by minimizing residuals between computed and actual fields. By compressing complex 3-D geometries to compact codes, the PADNN alleviates ill-posedness, while the PO approximation mitigates nonlinearity. Consequently, DeepDPO achieves faster convergence, enhanced accuracy, and eliminates the need for hard-to-obtain electromagnetic data in pretraining. Numerical results demonstrate notable improvements in computational efficiency, accuracy, and the ability to represent complex objects, offering a promising solution for 3-D ISPs with the potential for further integration of physical principles.
本文提出了一种新的深度学习(DL)框架,用于解决3-D逆散射问题(isp),旨在从散射电场中重建完美电导体(pec)的几何形状。isp具有固有的病态和非线性,这对传统方法和深度学习方法都提出了挑战。为了解决这个问题,我们提出了DeepDPO,这是一种自监督深度学习方法,它将传统基于模型方法的可靠性与基于学习方法的效率相结合。该框架采用概率自解码器神经网络(PADNN)进行有符号距离场(SDF)的连续几何表示,并结合基于网格的物理光学(PO)方法进行前向散射计算。通过PADNN对目标特定代码进行解码,并通过最小化计算字段与实际字段之间的残差来优化重建模型。通过将复杂的三维几何图形压缩成紧凑的编码,PADNN减轻了病态性,而PO近似减轻了非线性。因此,DeepDPO实现了更快的收敛,提高了精度,并且在预训练中消除了对难以获得的电磁数据的需求。数值结果表明,该方法在计算效率、精度和表示复杂对象的能力方面有了显著提高,为三维isp提供了一个有希望的解决方案,具有进一步整合物理原理的潜力。
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引用次数: 0
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IEEE Transactions on Antennas and Propagation
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