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Search Results (375)

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Keywords = flexible antenna

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14 pages, 1466 KiB  
Article
Miniaturized Arrow-Shaped Flexible Filter-Embedded Antenna for Industrial and Medical Applications
by Musa Hussain, Anees Abbas, Wahaj Abbas Awan and Syeda Iffat Naqvi
Appl. Sci. 2024, 14(23), 11004; https://doi.org/10.3390/app142311004 - 26 Nov 2024
Viewed by 325
Abstract
This paper presents the design and characterization of a coplanar waveguide (CPW) fed, low-profile, and flexible arrow-shaped filtenna for ISM band applications at 2.45 GHz. The antenna design involves an innovative approach incorporating etching slots to achieve miniaturization by 34%, contrasting with a [...] Read more.
This paper presents the design and characterization of a coplanar waveguide (CPW) fed, low-profile, and flexible arrow-shaped filtenna for ISM band applications at 2.45 GHz. The antenna design involves an innovative approach incorporating etching slots to achieve miniaturization by 34%, contrasting with a traditional quadrilateral-shaped antenna. After the attainment of desired miniaturization, the unwanted harmonics are also mitigated by deploying simple filtering methodology. A perpendicular rectangular stub is strategically introduced to the feedline, effectively minimizing harmonics across a broad frequency range of 3.3–11.0 GHz. Through simulations and measurements, the results indicate that the antenna’s operational band spans from 2.276 to 2.75 GHz, encompassing the entire ISM band (2.4–2.5 GHz). Notably, the antenna demonstrates promising radiation characteristics, including omnidirectional gain of approximately 2.2 dBi and a radiation efficiency exceeding 95%. With a compact overall size of 0.24λ × 0.20λ × 0.0005λ (where λ is the free-space wavelength at 2.45 GHz), coupled with wide harmonic rejection property, the proposed arrow-shaped flitenna emerges as a compelling candidate for ISM band applications. Full article
14 pages, 12233 KiB  
Article
A New Concept of Reconfigurable Antenna Structure Based on an Array of RF-MEMS Switches
by Massimo Donelli, Jacopo Iannacci and Mohammedhusen Manekiya
Appl. Sci. 2024, 14(23), 10941; https://doi.org/10.3390/app142310941 - 25 Nov 2024
Viewed by 285
Abstract
A geometrical reconfigurable structure based on RF Micro-electro-mechanical switches (RF-MEMS) is proposed in this work. The structure is composed of an array of gold metallic patches interconnected together utilizing RF-MEMS switches in order to change its geometry and, consequently, the scattering parameters. In [...] Read more.
A geometrical reconfigurable structure based on RF Micro-electro-mechanical switches (RF-MEMS) is proposed in this work. The structure is composed of an array of gold metallic patches interconnected together utilizing RF-MEMS switches in order to change its geometry and, consequently, the scattering parameters. In particular, the reconfigurability is achieved by activating multiple RF-MEMS switches, which enables the change in electrical length and, consequently, the resonance frequency of the structure. As a proof of concept, an experimental antenna prototype composed of an array of 7×7 elements interconnected by a set of RF-MEMS switches has been designed, fabricated numerically, and experimentally assessed. The structure can be set as an antenna or as other basic radio frequency components. The obtained experimental results are in good agreement with the simulations, with an error of less than 5% for the considered radiating structures. The quite promising results demonstrate the potential and flexibility of the proposed structure. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
17 pages, 7096 KiB  
Article
Knitted Microwave Transmission Line for Wearable Electronics
by Łukasz Januszkiewicz and Iwona Nowak
Appl. Sci. 2024, 14(23), 10798; https://doi.org/10.3390/app142310798 - 21 Nov 2024
Viewed by 385
Abstract
This paper introduces a novel approach to fabricating textile microwave transmission lines through knitting techniques. These textile-based transmission lines, capable of transmitting high-frequency signals between wearable transceivers and antennas, offer significant potential for the development of advanced wearable electronics. By leveraging a single [...] Read more.
This paper introduces a novel approach to fabricating textile microwave transmission lines through knitting techniques. These textile-based transmission lines, capable of transmitting high-frequency signals between wearable transceivers and antennas, offer significant potential for the development of advanced wearable electronics. By leveraging a single technological process, our proposed method enables the creation of flexible and wearable devices. To demonstrate the feasibility of this approach, we present the design and numerical modeling of a microstrip line operating within the gigahertz frequency range. A prototype structure was fabricated and experimentally characterized, revealing moderate attenuation of less than 5 dB for frequencies below 2.5 GHz. However, a major challenge in the field of wearable electronics is the real-time applicability of such devices. Our work aims to address this challenge by providing a flexible and scalable solution for integrating wireless communication capabilities into wearable systems. Future research will focus on further optimizing the design and fabrication processes to enhance performance and minimize signal loss, ultimately enabling the realization of practical and user-friendly wearable devices. Full article
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<p>Schematic view of the wearable wireless system with textile antenna and textile transmission line.</p>
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<p>Microstrip transmission line impedances and signal definition.</p>
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<p>Microstrip transmission line dimensions.</p>
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<p>Numerical model of microstrip transmission line (cross-section).</p>
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<p>The electric field intensity in the cross-section of the transmission line model at 2.5 GHz.</p>
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<p><span class="html-italic">S</span><sub>11</sub> obtained from simulations for tan (<span class="html-italic">δ</span>) = 0.05 and various <span class="html-italic">ε<sub>r</sub></span> parameters.</p>
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<p><span class="html-italic">S</span><sub>21</sub> obtained from simulations for <span class="html-italic">ε<sub>r</sub></span> = 1.5 and various values of the tg(<span class="html-italic">δ</span>) parameter.</p>
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<p>Spacer knitted fabric structure.</p>
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<p>The Mayer &amp; Co knitting machine used in the work to create a transmission line.</p>
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<p>Spacer knitted weaves: (<b>a</b>,<b>b</b>) plain stitch; (<b>c</b>) monofilament providing distance (not forming the knitted mesh).</p>
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<p>The knitted fabric: (<b>a</b>) top view showing the transmission path weave (top of the sample); (<b>b</b>) cross-section; (<b>c</b>) view of the bottom layer (ground plane).</p>
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<p>Prototype of the knitted transmission line: (<b>a</b>) top side; (<b>b</b>) bottom side (ground plane).</p>
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<p>Measurement setup for transmission line characterization.</p>
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<p><span class="html-italic">S</span><sub>11</sub> obtained from measurements of prototype line compared with results of simulations for <span class="html-italic">ε<sub>r</sub></span> = 1.5 and tg(<span class="html-italic">δ</span>) = 1.5.</p>
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<p><span class="html-italic">S</span><sub>21</sub> obtained from measurements of prototype line compared with results of simulations for <span class="html-italic">ε<sub>r</sub></span> = 1.5 and tg(<span class="html-italic">δ</span>) = 1.5.</p>
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<p>The experimental setup for convex bending.</p>
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<p>The experimental setup for concave bending.</p>
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<p>Measurement results of <span class="html-italic">S</span><sub>11</sub> parameter for bent transmission lines compared with a straight line.</p>
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<p>Measurement results of <span class="html-italic">S</span><sub>21</sub> parameter for bent transmission lines compared with a straight line.</p>
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27 pages, 6231 KiB  
Review
A Review of Unmanned Aerial Vehicle Based Antenna and Propagation Measurements
by Venkat R. Kandregula, Zaharias D. Zaharis, Qasim Z. Ahmed, Faheem A. Khan, Tian Hong Loh, Jason Schreiber, Alexandre Jean René Serres and Pavlos I. Lazaridis
Sensors 2024, 24(22), 7395; https://doi.org/10.3390/s24227395 - 20 Nov 2024
Viewed by 531
Abstract
This paper presents a comprehensive survey of state-of-the-art UAV–based antennas and propagation measurements. Unmanned aerial vehicles (UAVs) have emerged as powerful tools for in situ electromagnetic field assessments due to their flexibility, cost-effectiveness, and ability to operate in challenging environments. This paper highlights [...] Read more.
This paper presents a comprehensive survey of state-of-the-art UAV–based antennas and propagation measurements. Unmanned aerial vehicles (UAVs) have emerged as powerful tools for in situ electromagnetic field assessments due to their flexibility, cost-effectiveness, and ability to operate in challenging environments. This paper highlights various UAV applications, from testing large–scale antenna arrays, such as those used in the square kilometer array (SKA), to evaluating channel models for 5G/6G networks. Additionally, the review discusses technical challenges, such as positioning accuracy and antenna alignment, and it provides insights into the latest advancements in portable measurement systems and antenna designs tailored for UAV use. During the UAV–based antenna measurements, key contributors to the relatively small inaccuracies of around 0.5 to 1 dB are identified. In addition to factors such as GPS positioning errors and UAV vibrations, ground reflections can significantly contribute to inaccuracies, leading to variations in the measured radiation patterns of the antenna. By minimizing ground reflections during UAV–based antenna measurements, errors in key measured antenna parameters, such as HPBW, realized gain, and the front-to-back ratio, can be effectively mitigated. To understand the source of propagation losses in a UAV to ground link, simulations were conducted in CST. These simulations identified scattering effects caused by surrounding buildings. Additionally, by simulating a UAV with a horn antenna, potential sources of electromagnetic coupling between the antenna and the UAV body were detected. The survey concludes by identifying key areas for future research and emphasizing the potential of UAVs to revolutionize antenna and propagation measurement practices to avoid the inaccuracies of the antenna parameters measured by the UAV. Full article
(This article belongs to the Special Issue New Methods and Applications for UAVs)
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<p>Organization of the paper.</p>
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<p>Measurement configuration of the UAV system.</p>
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<p>Conventional elevated slant test range.</p>
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<p>UAV–based in situ measurement for a parabolic reflector antenna system.</p>
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<p>UAV–based measurement for a parabolic reflector antenna system placed on a ship.</p>
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<p>Vertical radiation pattern of a BASTA using a UAV.</p>
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<p>Horizontal radiation pattern of a BASTA using a UAV.</p>
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<p>Common errors in broadcasting systems.</p>
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<p>SixArms airborne measurements for broadcasting systems.</p>
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<p>(<b>a</b>) UAV–based measurements at 720 m and (<b>b</b>) UAV–based measurements at 2025 m.</p>
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<p>UAV–based measurements in radiating near field.</p>
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<p>UAV–based measurements for an array of HF wire biconical antennas.</p>
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<p>UAV with monopole flying over the LPDA array.</p>
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<p>Scattering effect in a semi–urban area simulated in CST.</p>
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<p>Hexacopter carrying cloverleaf wire antenna.</p>
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<p>Scattering effect in an urban area simulated in CST Studio Suite.</p>
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<p>Fields scattered by the UAV body.</p>
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28 pages, 8537 KiB  
Article
The Future of Radar Space Observation in Europe—Major Upgrade of the Tracking and Imaging Radar (TIRA)
by Jens Klare, Florian Behner, Claudio Carloni, Delphine Cerutti-Maori, Lars Fuhrmann, Clemens Hoppenau, Vassilis Karamanavis, Marcel Laubach, Alexander Marek, Robert Perkuhn, Simon Reuter and Felix Rosebrock
Remote Sens. 2024, 16(22), 4197; https://doi.org/10.3390/rs16224197 - 11 Nov 2024
Viewed by 1019
Abstract
The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they [...] Read more.
The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they can be operated at any time and under any weather conditions. The Tracking and Imaging Radar (TIRA) is one of the largest space observation radars in the world. It consists of a 34m Cassegrain antenna, a precise tracking radar, and a high-resolution imaging radar. Since the 1990s, TIRA contributes to the field of space domain awareness by tracking and imaging space objects and by monitoring the debris population. Due to new technologies, modern satellites become smaller, and satellite extensions become more compact. Thus, sensitive high-resolution space observation systems are needed to detect, track, and image these space objects. To fulfill these requirements, TIRA is undergoing a major upgrade. The current imaging radar in the Ku band will be replaced by a new radar with improved geometrical and radiometric resolution operating in the Ka band. Due to its wideband fully polarimetric capability, the new imaging radar will increase the analysis and characterization of space objects. In addition, the tracking radar in the L band is also being currently refurbished. Through its novel modular structure and open design, highly flexible radar modes and precise tracking concepts can be efficiently implemented for enhanced space domain awareness. The new TIRA system will mark the start of a new era for space observation with radar in Europe. Full article
(This article belongs to the Special Issue Radar for Space Observation: Systems, Methods and Applications)
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<p>Illustration of the Tracking and Imaging Radar, TIRA. The system’s 34 <math display="inline"><semantics> <mi mathvariant="normal">m</mi> </semantics></math> fully movable parabolic antenna and radar systems are protected by a 47.5 m radome. The surrounding 3-story building houses offices and laboratories associated with FHR’s research activities in SSA as well as technical infrastructure necessary for the operation of the TIRA system.</p>
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<p>Block diagram illustrating the current system architecture of TIRA. Components of the tracking radar are shown in dark blue, the imaging radar is show in turquoise, and common system components have a light blue background.</p>
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<p>Sentinel−3B (27 January 2021) [<a href="#B6-remotesensing-16-04197" class="html-bibr">6</a>].</p>
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<p>ELSA-D and ELSA-D CLIENT [<a href="#B10-remotesensing-16-04197" class="html-bibr">10</a>].</p>
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<p>Astroscale exercise (8 April 2022) [<a href="#B11-remotesensing-16-04197" class="html-bibr">11</a>].</p>
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<p>NILESAT cluster (16 March 2023).</p>
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<p>(<b>a</b>–<b>h</b>) Series of ISAR images of AEOLUS obtained during its last pass observed by TIRA on 28 July 2023 [<a href="#B13-remotesensing-16-04197" class="html-bibr">13</a>].</p>
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<p>Jason-2 (13 October 2022).</p>
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<p>Cosmos-1408 (1 December 2021) computed with an angular velocity of 92.3 deg/s.</p>
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<p>Tselina-D model [<a href="#B16-remotesensing-16-04197" class="html-bibr">16</a>].</p>
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<p>Atlas-5 Centaur rocket body (16 March 2023) [<a href="#B17-remotesensing-16-04197" class="html-bibr">17</a>].</p>
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<p>Photo of an Atlas-5 Centaur rocket body [<a href="#B18-remotesensing-16-04197" class="html-bibr">18</a>].</p>
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<p>United Nations Office for Outer Space Affairs’ (2024), with major processing by Our World in Data, “Annual number of objects launched into space—NOOSA” [dataset]. United Nations Office for Outer Space Affairs’ “Online Index of Objects Launched into Outer Space” [original data] [<a href="#B20-remotesensing-16-04197" class="html-bibr">20</a>].</p>
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<p>Bistatic polarized ISAR images of a space object.</p>
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<p>Block diagram illustrating the future TIRA system architecture for enhanced space observation capabilities as a research instrument and an operational radar system.</p>
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<p>Overview of the ARCADIA method for MBSE.</p>
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<p>Illustration of the digital twin and model-based design concepts using TIRA’s high-precision position control as an example.</p>
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<p>Principle integration of system models into the operational software of TIRA utilizing the open FMI standard.</p>
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<p>Orientation of the system’s azimuth axis in a global reference frame via local measurements against the true vertical.</p>
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<p>History of the measured deviation of the antenna’s azimuth axis from the true vertical.</p>
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<p>Block diagram of the new system architecture for the TIRA tracking radar implementing the software-defined radio principle (Depicted satellite: Trisat, CC BY-SA 4.0 <a href="https://creativecommons.org/licenses/by-sa/4.0" target="_blank">https://creativecommons.org/licenses/by-sa/4.0</a>, accessed on 29 October 2024, via Wikimedia Commons).</p>
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<p>Modeled specific attenuation for precipitation, liquid water, and atmospheric gases with different relative humidity and temperature values along the ITU-assigned IEEE radar bands.</p>
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<p>Geometry of the angles <math display="inline"><semantics> <mi>ϑ</mi> </semantics></math> and <math display="inline"><semantics> <mi>α</mi> </semantics></math>. <math display="inline"><semantics> <mi>ϑ</mi> </semantics></math> is the 3 dB beam width of the antenna. <math display="inline"><semantics> <mi>α</mi> </semantics></math> is the angle between the antenna pointing direction and the line of sight to the satellite with the origin at the radar.</p>
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<p>Beam’s pointing accuracy of the TIRA system during a standard tracking observation.</p>
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<p>Principle block diagram of the high-power polarimetric quasi-optical monopulse front end.</p>
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24 pages, 626 KiB  
Article
Joint Design of Altitude and Channel Statistics Based Energy Beamforming for UAV-Enabled Wireless Energy Transfer
by Jinho Kang
Drones 2024, 8(11), 668; https://doi.org/10.3390/drones8110668 - 11 Nov 2024
Viewed by 536
Abstract
In recent years, UAV-enabled wireless energy transfer (WET) has attracted significant attention for its ability to provide ground devices with efficient and stable power by flexibly navigating three-dimensional (3D) space and utilizing favorable line-of-sight (LoS) channels. At the same time, energy beamforming utilizing [...] Read more.
In recent years, UAV-enabled wireless energy transfer (WET) has attracted significant attention for its ability to provide ground devices with efficient and stable power by flexibly navigating three-dimensional (3D) space and utilizing favorable line-of-sight (LoS) channels. At the same time, energy beamforming utilizing multiple antennas, in which energy beams are focused toward devices in desirable directions, has been highlighted as a key technology for substantially enhancing radio frequency (RF)-based WET efficiency. Despite its significant utility, energy beamforming has not been studied in the context of UAV-enabled WET system design. In this paper, we propose the joint design of UAV altitude and channel statistics based energy beamforming to minimize the overall charging time required for all energy-harvesting devices (EHDs) to meet their energy demands while reducing the additional resources and costs associated with channel estimation. Unlike previous works, in which only the LoS dominant channel without small-scale fading was considered, we adopt a more general air-to-ground (A2G) Rician fading channel, where the LoS probability as well as the Rician factor is dependent on the UAV altitude. To tackle this highly nonconvex and nonlinear design problem, we first examine the scenario of a single EHD, drawing insights by deriving an optimal energy beamforming solution in closed form. We then devise efficient methods for jointly designing altitude and energy beamforming in scenarios with multiple EHDs. Our numerical results demonstrate that the proposed joint design considerably reduces the overall charging time while significantly lowering the computational complexity compared to conventional methods. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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<p>Illustration of our system model.</p>
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<p>Comparison of the objective function for different horizontal distances of the EHD.</p>
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<p>Comparison of the optimal UAV altitude determined by the 1D exhaustive line search method (Algorithm 1) and the proposed method (Algorithm 2).</p>
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<p>Average UAV altitude and its standard deviation via various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> m in an Urban environment.</p>
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<p>Performance comparison of various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> m in an Urban environment.</p>
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<p>Average UAV altitude and its standard deviation via various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> m in an Urban environment.</p>
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<p>Performance comparison of various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> m in an Urban environment.</p>
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<p>Performance comparison of various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> m in a Dense Urban environment.</p>
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<p>Performance comparison of various methods when <math display="inline"><semantics> <mrow> <msub> <mi>r</mi> <mo movablelimits="true" form="prefix">max</mo> </msub> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> m in a Dense Urban environment.</p>
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17 pages, 34163 KiB  
Article
Analysis of 3D Printed Dielectric Resonator Antenna Arrays for Millimeter-Wave 5G Applications
by Siyu Li, Benito Sanz Izquierdo, Steven Gao and Zhijiao Chen
Appl. Sci. 2024, 14(21), 9886; https://doi.org/10.3390/app14219886 - 29 Oct 2024
Viewed by 573
Abstract
This paper explores the potential use of fused deposition modeling (FDM) technology for manufacturing microwave and millimeter-wave dielectric resonator antennas (DRAs) for 5G and beyond communication systems. DRAs operating at microwave and millimeter-wave (mmWave) frequency bands were simulated, fabricated, and analyzed in terms [...] Read more.
This paper explores the potential use of fused deposition modeling (FDM) technology for manufacturing microwave and millimeter-wave dielectric resonator antennas (DRAs) for 5G and beyond communication systems. DRAs operating at microwave and millimeter-wave (mmWave) frequency bands were simulated, fabricated, and analyzed in terms of manufacturing quality and radio frequency (RF) performance. Samples were manufactured using a 3D printer and PREPERM® ABS1000 filament, which offers a stable dielectric constant (εr = 10 ± 0.35) and low losses (tan δ = 0.003) over wide frequency and temperature ranges. Surface profile tests and microscope measurements revealed discrepancies in the dimensions in the xy-plane and along the z-axis, consistent with the observed shift in resonant frequency. Despite these variations, reasonably good agreement between RF-simulated and measured results was achieved, and the DRA array successfully covered the intended mmWave band. However, challenges in achieving high precision may restrict applications at higher mmWave bands. Nevertheless, compared with conventional methods, FDM techniques offer a highly accessible and flexible solution with a wide range of materials for home and micro-manufacturing of mmWave DRAs for modern 5G systems. Full article
(This article belongs to the Special Issue 5G and Beyond: Technologies and Communications)
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<p>Configuration of the FDM printed microwave DRA: (<b>a</b>) DRA on top of a metallic ground plane, (<b>b</b>) substrate and DRA made transparent to show the microstrip transmission line on the back of the substrate and the slot on the top ground plane.</p>
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<p>Zoom-in view of the top and bottom surfaces of the FDM-printed microwave DRA. (<b>a</b>) top view, (<b>b</b>) bottom view.</p>
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<p>2D cut surface profile of the FDM-printed DRA.</p>
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<p>3D side view and 2D cut surface profile of the FDM-printed DRA.</p>
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<p>Fabricated DRA. (<b>a</b>) top view, (<b>b</b>) bottom view.</p>
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<p>Simulated and measured <span class="html-italic">S</span><sub>11</sub> of the microwave DRA design. Adjusted dimensional parameters and permittivity were also taken into account based on the measured values.</p>
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<p>Configuration of the mmWave DRA array.</p>
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<p>Simulated efficiency and realized gain for mmWave DRA array.</p>
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<p>Beam scanning performance of the DRA array in (<b>a</b>) xz- and (<b>b</b>) yz-plane.</p>
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<p>Gain at broadside direction with different (<b>a</b>) radius, (<b>b</b>) height, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ε</mi> </mrow> <mrow> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) tan <span class="html-italic">δ</span> of DRA element.</p>
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<p>Efficiency with different (<b>a</b>) radius, (<b>b</b>) height, (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ε</mi> </mrow> <mrow> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>d</b>) tan <span class="html-italic">δ</span> of DRA element.</p>
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<p>Configuration of the DRA array with an in-phase feeding network.</p>
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<p>Photographs of the FDM 3D-printed DRA array with an in-phase feeding network. (<b>a</b>) top view, (<b>b</b>) bottom view.</p>
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<p>Zoom-in view of the top and bottom surfaces of the FDM 3D-printed mmWave DRA. (<b>a</b>) top view, (<b>b</b>) bottom view.</p>
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<p>2D cut surface profile of the FDM-printed mmWave DRA.</p>
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<p>3D side view and 2D cut surface profile of the FDM-printed mmWave DRA element.</p>
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<p>Simulated and measured matching performance of the FDM 3D-printed DRA array with in-phase feeding network.</p>
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<p>Simulated and measured radiation patterns of the FDM 3D-printed DRA array at 26.8 GHz. (<b>a</b>) xz- and (<b>b</b>) yz-plane.</p>
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<p>Simulated and measured realized gain at the broadside direction of the FDM 3D-printed DRA array.</p>
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<p>(<b>a</b>) Configuration of the DRA array, and (<b>b</b>) simulated efficiency and realized gain.</p>
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<p>Beam scanning performance of the cuboid DRA array in the (<b>a</b>) xz-, and (<b>b</b>) yz-planes.</p>
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<p>Top view of the FDM 3D-printed cuboid DRA element (<b>a</b>) before, and (<b>b</b>) after refining.</p>
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<p>Side view of the FDM 3D-printed cuboid DRA element (<b>a</b>) before, and (<b>b</b>) after refining.</p>
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14 pages, 1518 KiB  
Article
Software-Defined Platform for Global Navigation Satellite System Antenna Array Development and Testing
by Diogo Gomes, Diogo Baptista, Hugo Dinis, Paulo M. Mendes and Sérgio Lopes
Appl. Sci. 2024, 14(21), 9621; https://doi.org/10.3390/app14219621 - 22 Oct 2024
Viewed by 795
Abstract
With the increasing demand for accurate and robust positioning solutions, the use of GNSS antenna arrays has gained significant attention. However, their development and testing are frequently constrained by the inflexibility of traditional hardware platforms, often requiring extensive reconfiguration throughout the development cycle. [...] Read more.
With the increasing demand for accurate and robust positioning solutions, the use of GNSS antenna arrays has gained significant attention. However, their development and testing are frequently constrained by the inflexibility of traditional hardware platforms, often requiring extensive reconfiguration throughout the development cycle. This paper presents a platform based on a system on chip to develop a highly flexible software-controlled system that is capable of directly sampling up to 16 antenna elements. Multibeam digital beamforming is implemented using the available FPGA resources and the resulting signal is reproduced by the integrated DAC and can be connected to any conventional single antenna GNSS receiver. This paper presents the architecture of the platform, detailing its components and capabilities. Our experimental results demonstrate that the system can phase shift every channel with errors of less than 0.5° and can reconfigure 4 simultaneous beams of a 16-antenna array at speeds of 1.2 kHz, and 20 beams at around 400 Hz. The average delay introduced by each channel of the system is around 381 ns with a maximum deviation of 1.05 ns. The delay was also measured for the implementation using 4 beams, which achieves a slightly bigger average delay of 384.6 ns while keeping the variation to 5 to 6 ns. This system is intended to be used as the backbone for the development of antenna arrays and beamforming algorithms. Given its flexibility, it is not necessary to develop new hardware between development iterations or even for different systems, as only the software layer needs to be modified. Consequently, it is possible to expedite the development stage before producing dedicated solutions for industrial applications. Full article
(This article belongs to the Special Issue Advanced Antenna Array Technologies and Applications)
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<p>Block diagram of the SDA system.</p>
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<p>Measured S<sub>21</sub> parameters of the FPGA’s 16 channels; a demonstration that the board’s current configuration can process signals in the 1.45–1.7 GHz range.</p>
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<p>Block diagram of the developed system.</p>
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<p>Second Nyquist zone sampling of the L1/E1 band.</p>
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<p>Mixing the signal to baseband.</p>
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<p>Implementation of the multibeam IP core.</p>
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<p>Group delay results for L1/E1 frequency bandwidth.</p>
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25 pages, 13404 KiB  
Article
Drone SAR Imaging for Monitoring an Active Landslide Adjacent to the M25 at Flint Hall Farm
by Anthony Carpenter, James A. Lawrence, Philippa J. Mason, Richard Ghail and Stewart Agar
Remote Sens. 2024, 16(20), 3874; https://doi.org/10.3390/rs16203874 - 18 Oct 2024
Viewed by 977
Abstract
Flint Hall Farm in Godstone, Surrey, UK, is situated adjacent to the London Orbital Motorway, or M25, and contains several landslide systems which pose a significant geohazard risk to this critical infrastructure. The site has been routinely monitored by geotechnical engineers following a [...] Read more.
Flint Hall Farm in Godstone, Surrey, UK, is situated adjacent to the London Orbital Motorway, or M25, and contains several landslide systems which pose a significant geohazard risk to this critical infrastructure. The site has been routinely monitored by geotechnical engineers following a landslide that encroached onto the hard shoulder in December 2000; current in situ instrumentation includes inclinometers and piezoelectric sensors. Interferometric Synthetic Aperture Radar (InSAR) is an active remote sensing technique that can quantify millimetric rates of Earth surface and structural deformation, typically utilising satellite data, and is ideal for monitoring landslide movements. We have developed the hardware and software for an Unmanned Aerial Vehicle (UAV), or drone radar system, for improved operational flexibility and spatial–temporal resolutions in the InSAR data. The hardware payload includes an industrial-grade DJI drone, a high-performance Ettus Software Defined Radar (SDR), and custom Copper Clad Laminate (CCL) radar horn antennas. The software utilises Frequency Modulated Continuous Wave (FMCW) radar at 5.4 GHz for raw data collection and a Range Migration Algorithm (RMA) for focusing the data into a Single Look Complex (SLC) Synthetic Aperture Radar (SAR) image. We present the first SAR image acquired using the drone radar system at Flint Hall Farm, which provides an improved spatial resolution compared to satellite SAR. Discrete targets on the landslide slope, such as corner reflectors and the in situ instrumentation, are visible as bright pixels, with their size and positioning as expected; the surrounding grass and vegetation appear as natural speckles. Drone SAR imaging is an emerging field of research, given the necessary and recent technological advancements in drones and SDR processing power; as such, this is a novel achievement, with few authors demonstrating similar systems. Ongoing and future work includes repeat-pass SAR data collection and developing the InSAR processing chain for drone SAR data to provide meaningful deformation outputs for the landslides and other geotechnical hazards and infrastructure. Full article
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<p>Flint Hall Farm study area (hatched red pattern), with annotated M25, Godstone, and regional UK overview map.</p>
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<p>Flint Hall Farm study area (hatched red pattern), with 1 m LiDAR Composite DTM for elevation and labelled contour lines.</p>
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<p>Zones and sub-zones at the Flint Hall Farm site, including the Flint Hall Farm Zone, Zones 1–3 (red); the Midslope Zone, Zones 1–2 (blue); and, the Rooks Nest Farm Zone, Zones 1–4 (yellow) [<a href="#B25-remotesensing-16-03874" class="html-bibr">25</a>]. The zone colour shading is more transparent than the legend colours for surface feature visibility.</p>
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<p>Landslide extents at the Flint Hall Farm site, including the Flint Hall Farm, Flint Hall Farm South, and Rooks Nest Farm Landslides [<a href="#B25-remotesensing-16-03874" class="html-bibr">25</a>].</p>
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<p>Simplified geological map of the study area, with Flint Hall Farm (red circle), and a geological cross-section for line A–A′ (green circle). Adapted from [<a href="#B26-remotesensing-16-03874" class="html-bibr">26</a>].</p>
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<p>Schematic of the Flint Hall Farm landslide, which occurred on 19 December 2000 [<a href="#B1-remotesensing-16-03874" class="html-bibr">1</a>].</p>
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<p>Geological cross-section schematic of the Flint Hall Farm landslide, which occurred on 19 December 2000 [<a href="#B1-remotesensing-16-03874" class="html-bibr">1</a>].</p>
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<p>Corner reflectors at Flint Hall Farm, with annotated M25.</p>
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<p>Photographs of the CCL horn antennas: (<b>a</b>) external view; (<b>b</b>) internal view.</p>
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<p>Drone radar payload, with the CCL horn antennas, E312 SDR and 3D-printed connection stabiliser for the SMB-SMA connectors, and Raspberry Pi (on the back).</p>
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<p>Drone radar payload attached to the drone at Flint Hall Farm.</p>
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<p>FMCW modulation: (<b>a</b>) amplitude domain; (<b>b</b>) frequency domain, where transmission (Tx) is red, and reception (Rx) is green.</p>
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<p>FMCW radar block diagram.</p>
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<p>RMA block diagram.</p>
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<p>Schematic of drone flight geometry with corner reflector target.</p>
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<p>Photograph of the drone radar system in-flight at Flint Hall Farm.</p>
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<p>(<b>a</b>) SLC SAR image from Flint Hall Farm, with annotated flight path and circled targets; the latter includes the corner reflectors (red), and other fenced areas for in situ instrumentation (yellow, blue and pink); (<b>b</b>) Google Street View imagery of Flint Hall Farm, with annotated flight path, and corresponding circled targets, as indicated by the arrows connecting (<b>a</b>,<b>b</b>).</p>
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<p>Average SAR amplitude for Flint Hall Farm (white boundary) from September 2021 to September 2023, with annotated M25 and Godstone. The zoomed image boundary is denoted by the red box. The corner reflector and in situ instrumental pixels are circled in blue.</p>
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<p>Side-by-side comparison of (<b>a</b>) average SAR amplitude for Flint Hall Farm (white boundary) from September 2021 to September 2023; the corner reflector and in situ instrumental pixels are circled in blue, and (<b>b</b>) drone SAR image from Flint Hall Farm, with circled targets, including the corner reflectors (red), and other fenced areas for in situ instrumentation (yellow, blue, and pink).</p>
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17 pages, 4291 KiB  
Article
Deep-Unfolded Tikhonov-Regularized Conjugate Gradient Algorithm for MIMO Detection
by Sümeye Nur Karahan and Aykut Kalaycıoğlu
Electronics 2024, 13(19), 3945; https://doi.org/10.3390/electronics13193945 - 7 Oct 2024
Viewed by 753
Abstract
In addressing the multifaceted problem of multiple-input multiple-output (MIMO) detection in wireless communication systems, this work highlights the pressing need for enhanced detection reliability under variable channel conditions and MIMO antenna configurations. We propose a novel method that sets a new standard for [...] Read more.
In addressing the multifaceted problem of multiple-input multiple-output (MIMO) detection in wireless communication systems, this work highlights the pressing need for enhanced detection reliability under variable channel conditions and MIMO antenna configurations. We propose a novel method that sets a new standard for deep unfolding in MIMO detection by integrating the iterative conjugate gradient method with Tikhonov regularization, combining the adaptability of modern deep learning techniques with the robustness of classical regularization. Unlike conventional techniques, our strategy treats the Tikhonov regularization parameter, as well as the step size and search direction coefficients of the conjugate gradient (CG) method, as trainable parameters within the deep learning framework. This enables dynamic adjustments based on varying channel conditions and MIMO antenna configurations. Detection performance is significantly improved by the proposed approach across a range of MIMO configurations and channel conditions, consistently achieving lower bit error rate (BER) and normalized minimum mean square error (NMSE) compared to well-known techniques like DetNet and CG. The proposed method has superior performance over CG and other model-based methods, especially with a small number of iterations. Consequently, the simulation results demonstrate the flexibility of the proposed approach, making it a viable choice for MIMO systems with a range of antenna configurations, modulation orders, and different channel conditions. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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<p>Simplified block diagram of a MIMO system.</p>
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<p>LCG algorithm in <span class="html-italic">i<sup>th</sup></span> layer.</p>
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<p>DU-TCG algorithm in <b><span class="html-italic">i<sup>th</sup></span></b> layer.</p>
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<p>BER performance for a 10 × 10 MIMO system.</p>
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<p>BER performance for different number of layers: (<b>a</b>) 5 layers; (<b>b</b>) 15 layers.</p>
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<p>BER performance over different channel models: Kronecker, TDL-A, and TDL-E.</p>
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<p>BER performance for different modulation types: (<b>a</b>) BPSK; (<b>b</b>) 16-QAM.</p>
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<p>BER performance for different higher-order modulation types.</p>
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<p>BER performance between DU-TCG and DetNet in a 32 × 64 MIMO system.</p>
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<p>NMSE performance: (<b>a</b>) scalar parameterization; (<b>b</b>) vector parameterization.</p>
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<p>BER performance with scalar and vector parameterization in 32 × 64 Rayleigh channel.</p>
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19 pages, 6453 KiB  
Article
A Versatile, Machine-Learning-Enhanced RF Spectral Sensor for Developing a Trunk Hydration Monitoring System in Smart Agriculture
by Oumaima Afif, Leonardo Franceschelli, Eleonora Iaccheri, Simone Trovarello, Alessandra Di Florio Di Renzo, Luigi Ragni, Alessandra Costanzo and Marco Tartagni
Sensors 2024, 24(19), 6199; https://doi.org/10.3390/s24196199 - 25 Sep 2024
Viewed by 3339
Abstract
This paper comprehensively explores the development of a standalone and compact microwave sensing system tailored for automated radio frequency (RF) scattered parameter acquisitions. Coupled with an emitting RF device (antenna, resonator, open waveguide), the system could be used for non-invasive monitoring of external [...] Read more.
This paper comprehensively explores the development of a standalone and compact microwave sensing system tailored for automated radio frequency (RF) scattered parameter acquisitions. Coupled with an emitting RF device (antenna, resonator, open waveguide), the system could be used for non-invasive monitoring of external matter or latent environmental variables. Central to this design is the integration of a NanoVNA and a Raspberry Pi Zero W platform, allowing easy recording of S-parameters (scattering parameters) in the range of the 50 kHz–4.4 GHz frequency band. Noteworthy features include dual recording modes, manual for on-demand acquisitions and automatic for scheduled data collection, powered seamlessly by a single battery source. Thanks to the flexibility of the system’s architecture, which embeds a Linux operating system, we can easily embed machine learning (ML) algorithms and predictive models for information detection. As a case study, the potential application of the integrated sensor system with an RF patch antenna is explored in the context of greenwood hydration detection within the field of smart agriculture. This innovative system enables non-invasive monitoring of wood hydration levels by analyzing scattering parameters (S-parameters). These S-parameters are then processed using ML techniques to automate the monitoring process, enabling real-time and predictive analysis of moisture levels. Full article
(This article belongs to the Special Issue AI, IoT and Smart Sensors for Precision Agriculture)
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<p>Overview of the proposed system and application.</p>
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<p>(<b>a</b>) Hardware structure of the proposed PCB; (<b>b</b>) data flow scheme.</p>
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<p>PCB and case implementation: (<b>a</b>) front view; (<b>b</b>) back view; (<b>c</b>) side front view; (<b>d</b>) side back view; and (<b>e</b>) case made using 3D printing.</p>
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<p>(<b>a</b>) Top view; (<b>b</b>) lateral view of the proposed antenna with its dimensions (<math display="inline"><semantics> <mrow> <mi>W</mi> <mo>=</mo> <mi>L</mi> <mo>=</mo> </mrow> </semantics></math> 50 mm, <math display="inline"><semantics> <mrow> <msub> <mi>W</mi> <mi>p</mi> </msub> <mo>=</mo> <msub> <mi>L</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>24.4</mn> </mrow> </semantics></math> mm, and <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi mathvariant="normal">s</mi> </msub> <mo>=</mo> <mn>0.61</mn> </mrow> </semantics></math> mm); and (<b>c</b>) simulated reflection coefficient in three different loading conditions: free-space scenario, dry wood loaded, and wet wood loaded.</p>
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<p>Mode of acquisitions: (<b>a</b>) <span class="html-italic">manual</span>; (<b>b</b>) <span class="html-italic">automatic</span>.</p>
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<p>Experimental setup comprising a patch antenna, a drying oven, a greenwood sample, and the customized PCB.</p>
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<p>Drying curve of the greenwood on a dry basis vs. time.</p>
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<p>PLSR scheme for calibration, CV, and test validation.</p>
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<p>(<b>a</b>) Magnitude of <math display="inline"><semantics> <msub> <mi>S</mi> <mn>11</mn> </msub> </semantics></math>; (<b>b</b>) its derivative highlights differences in spectra due to MC change.</p>
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<p>Predicted versus observed MC (in %) for test and calibration of PLSR</p>
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<p>Regression coefficient <math display="inline"><semantics> <mi>β</mi> </semantics></math> for <math display="inline"><semantics> <msub> <mi>S</mi> <mn>11</mn> </msub> </semantics></math> and its derivative.</p>
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19 pages, 6389 KiB  
Article
A Breast Tumor Monitoring Vest with Flexible UWB Antennas—A Proof-of-Concept Study Using Realistic Breast Phantoms
by Rakshita Dessai, Daljeet Singh, Marko Sonkki, Jarmo Reponen, Teemu Myllylä, Sami Myllymäki and Mariella Särestöniemi
Micromachines 2024, 15(9), 1153; https://doi.org/10.3390/mi15091153 - 14 Sep 2024
Viewed by 1008
Abstract
Breast cancers can appear and progress rapidly, necessitating more frequent monitoring outside of hospital settings to significantly reduce mortality rates. Recently, there has been considerable interest in developing techniques for portable, user-friendly, and low-cost breast tumor monitoring applications, enabling frequent and cost-efficient examinations. [...] Read more.
Breast cancers can appear and progress rapidly, necessitating more frequent monitoring outside of hospital settings to significantly reduce mortality rates. Recently, there has been considerable interest in developing techniques for portable, user-friendly, and low-cost breast tumor monitoring applications, enabling frequent and cost-efficient examinations. Microwave technique-based breast cancer detection, which is based on differential dielectric properties of malignant and healthy tissues, is regarded as a promising solution for cost-effective breast tumor monitoring. This paper presents the development process of the first proof-of-concept of a breast tumor monitoring vest which is based on the microwave technique. Two unique vests are designed and evaluated on realistic 3D human tissue phantoms having different breast density types. Additionally, the measured results are verified using simulations carried out on anatomically realistic voxel models of the electromagnetic simulations. The radio channel characteristics are evaluated and analyzed between the antennas embedded in the vest in tumor cases and reference cases. Both measurements and simulation results show that the proposed vest can detect tumors even if only 1 cm in diameter. Additionally, simulation results show detectability with 0.5 cm tumors. It is observed that the detectability of breast tumors depends on the frequency, antenna selection, size of the tumors, and breast types, causing differences of 0.5–30 dB in channel responses between the tumorous and reference cases. Due to simplicity and cost-efficiency, the proposed channel analysis-based breast monitoring vests can be used for breast health checks in smaller healthcare centers and for user-friendly home monitoring which can prove beneficial in rural areas and developing countries. Full article
(This article belongs to the Special Issue Biomaterials, Biodevices and Tissue Engineering, Second Edition)
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<p>(<b>a</b>) Three cylindrical-shaped glandular phantoms: (1) reference, (2) with 1 cm tumor, and (3) with a 2 cm tumor; (<b>b</b>) breast phantom “Very Dense” with 0.5 cm thick fat layer; (<b>c</b>) breast phantom “Dense” with the glandular phantom inserted into the fat phantom; (<b>d</b>) measurement setup with phantoms set on the mannequin torso (1), above which the muscle phantom is first assembled (2), fat (3), glandular (4), and skin (5) phantoms [<a href="#B30-micromachines-15-01153" class="html-bibr">30</a>].</p>
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<p>Antennas used in the vest. (<b>a</b>) UWB monopole antenna design, (<b>b</b>) UWB monopole with flexible laminate substrate, (<b>c</b>) UWB monopole with conductive textile material, (<b>d</b>) Kapton polyamide substrate-based larger monopole [<a href="#B31-micromachines-15-01153" class="html-bibr">31</a>].</p>
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<p>(<b>a</b>) Tissue layer model used in antenna characteristics simulations, (<b>b</b>) S11 parameters of small and larger flexible antennas, (<b>c</b>–<b>h</b>) radiation patterns of small flexible antenna (left side of figure) and larger flexible antenna (right side of figure) at 3 GHz, 5 GHz, and 7 GHz.</p>
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<p>(<b>a</b>) Tissue layer model used in antenna characteristics simulations, (<b>b</b>) S11 parameters of small and larger flexible antennas, (<b>c</b>–<b>h</b>) radiation patterns of small flexible antenna (left side of figure) and larger flexible antenna (right side of figure) at 3 GHz, 5 GHz, and 7 GHz.</p>
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<p>The developed breast tumor monitoring vest types used in the evaluations: (<b>a</b>) Vest I with smaller flexible antennas and (<b>b</b>) Vest II with larger flexible antennas [<a href="#B31-micromachines-15-01153" class="html-bibr">31</a>]. The numbers above the antenna pockets indicate the antenna number.</p>
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<p>(<b>a</b>) Emma (<b>left</b>) and Laura (<b>right</b>) voxel models used in the simulations, (<b>b</b>) cross-section of Emma voxel (scattered fibroglandular tissue, <b>left</b>) and cross-section of Laura voxel (heterogeneous glandular breast tissue, <b>right</b>).</p>
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<p>Channel evaluations between (<b>a</b>) antennas 2 and 5 (Case 1a) and (<b>b</b>) antennas 2 and 7 (Case 1b) for Vest I with Antenna 1 and “Dense” breast phantom.</p>
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<p>Channel evaluations between the (<b>a</b>) antennas 2 and 5 (Case 2a) and (<b>b</b>) antennas 2 and 7 (Case 2b) for Vest I with Antenna 1 and “Less Dense” breast phantom.</p>
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<p>Channel evaluations in Case 3 between the (<b>a</b>) antennas 2 and 5 (Case 3a) and (<b>b</b>) antennas 2 and 7 (Case 3b) for Vest I with Antenna 2 and “Dense” breast phantom.</p>
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<p>Channel evaluations between in Case 4 (<b>a</b>) antennas 2 and 5 (Case 4a) and (<b>b</b>) antennas 2 and 7 (Case 4b) for Vest I with Antenna 2 and “Less Dense” breast phantom.</p>
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<p>Channel evaluations for Case 5 between the (<b>a</b>) antennas 1 and 6 (Case 5a) and (<b>b</b>) antennas 3 and 6 (Case 5b) for Vest II with Antenna 3 and “Dense” breast phantom.</p>
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<p>Channel evaluations for Case 6 between (<b>a</b>) antennas 1 and 6 (Case 6a) and (<b>b</b>) antennas 3 and 6 (Case 6b) for Vest II with Antenna 3 and “Less Dense” breast phantom.</p>
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<p>Case 7: Simulation-based channel evaluations with different tumor sizes: (<b>a</b>) S26 results using Emma voxel (Case 7a) and (<b>b</b>) S16 results using Laura voxel (Case 7b).</p>
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<p>Time-domain channel evaluations with different tumor sizes and different IFFT lengths: (<b>a</b>) Impulse response IR26 results using Emma voxel with full band IFFT conversion, (<b>b</b>) IR16 results using Laura voxel, with full band IFFT conversion, (<b>c</b>) IR16 results using Laura, with IFFT conversion to 4.5–5.8 GHz.</p>
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14 pages, 1503 KiB  
Article
Design of Typhoon Detection Downcast Device Based on Four-Arm Helical Antenna Structure
by Tao Hong, Zhiyan Lin, Yi Li and Tong Liu
Appl. Sci. 2024, 14(17), 7956; https://doi.org/10.3390/app14177956 - 6 Sep 2024
Viewed by 508
Abstract
The use of airships to launch space probes has been an effective means of conducting typhoon surveys in recent years, but the carrying area and weight of airships are very limited, so it is necessary to reduce the weight and volume of the [...] Read more.
The use of airships to launch space probes has been an effective means of conducting typhoon surveys in recent years, but the carrying area and weight of airships are very limited, so it is necessary to reduce the weight and volume of the release device as much as possible. This paper reports the first use of a probe with cylindrical and omnidirectional characteristics, as well as a four-arm spiral receiving antenna, which can also act as the downward release device of the inner wall and improve the space utilization rate. Through further analysis and improvement, it was determined that the four-armed helical antenna can be printed on the medium using a flexible material, which not only reduces the weight of the device but also avoids direct contact between the antenna and the sounding device and improves the stability of the antenna. The designed antenna was modeled and simulated using Ansys HFSS 2021 simulation software.The simulation results show that the antenna presented in this study achieves good performance at the center frequency of 403 MHz, the input voltage VSWR and return loss of the antenna are ideal, and the antenna has a good directional map. Full article
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<p>Schematic representation of airship sounding (color).</p>
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<p>Outline and internal structure of the sounder.</p>
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<p>Schematic diagram of a four-armed helical antenna.</p>
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<p>Decomposition schematic of the structure of the four-armed helical antenna.</p>
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<p>Decomposition schematic of the structure of the four-armed helical antenna.</p>
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<p>Equivalent model of four-armed helical antenna.</p>
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<p>HFSS modeling of the completed four-armed helical antenna.</p>
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<p>Return loss.</p>
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<p>Voltage VSWR.</p>
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<p>Radiation pattern.</p>
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<p>Overall schematic diagram of the droppable sounding system.</p>
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<p>Overall schematic of the improved droppable sounding system.</p>
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<p>Return loss.</p>
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<p>Voltage VSWR.</p>
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<p>Radiation pattern.</p>
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<p>Axial ratio.</p>
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22 pages, 1872 KiB  
Article
Sensing-Efficient Transmit Beamforming for ISAC with MIMO Radar and MU-MIMO Communication
by Huimin Liu, Yong Li, Wei Cheng, Limeng Dong and Beiming Yan
Remote Sens. 2024, 16(16), 3028; https://doi.org/10.3390/rs16163028 - 18 Aug 2024
Viewed by 990
Abstract
We focus on an integrated sensing and communication (ISAC) system—a single platform equipped with multiple antennas transmitting a waveform to detect targets and communicate with downlink users. Due to spectrum sharing between multiple-input–multiple-output (MIMO) radar and multiuser MIMO (MU-MIMO) communication, beamforming is becoming [...] Read more.
We focus on an integrated sensing and communication (ISAC) system—a single platform equipped with multiple antennas transmitting a waveform to detect targets and communicate with downlink users. Due to spectrum sharing between multiple-input–multiple-output (MIMO) radar and multiuser MIMO (MU-MIMO) communication, beamforming is becoming increasingly important as a technique that enables the creation of directional beams. In this paper, we propose a novel joint transmit beamforming design scheme that employs a beam pattern approximation strategy for radar sensing and utilizes rate-splitting for multiuser communication offering advanced interference management strategies. The optimization problems are formulated from both radar-centric and trade-off viewpoints. First, we propose a radar-centric beamforming scheme to achieve sensing efficiency through beam pattern approximation, while requiring the fairness signal-to-interference-plus-noise ratio (SINR) to be higher than a given threshold to guarantee a minimal level of communication quality, while the obtained performance for the communication system is limited in this scheme. To address this problem, we propose a beamforming design scheme from a trade-off viewpoint that flexibly optimizes both sensing and communication performances with a regularization parameter. Finally, we propose a partial rate-splitting-based beamforming design method aimed at maximizing the effective sensing power, with the constraint of a minimal sum rate for downlink users. Numerical results are provided to assess the effectiveness of all proposed schemes. Full article
(This article belongs to the Topic Radar Signal and Data Processing with Applications)
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<p>The ISAC system model simultaneously detects targets and communicates with multiple users.</p>
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<p>P-RS-aided ISAC scheme: (<b>a</b>) Transmitter; (<b>b</b>) Communication receiver.</p>
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<p>Radar beam pattern comparisons for <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>1</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math> with different number of downlink users: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>.</p>
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<p>Detection probability comparison under a false alarm probability of <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>1</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>, for <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>.</p>
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<p>Achievable WSR versus SINR threshold <math display="inline"><semantics> <mo>Γ</mo> </semantics></math>.</p>
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<p>WSR versus MSE of radar beam pattern.</p>
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<p>Achievable WSR versus SINR threshold <math display="inline"><semantics> <mo>Γ</mo> </semantics></math>.</p>
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<p>Feasible probability comparison between SDR and WMMSE-SDR (<b>a</b>) <math display="inline"><semantics> <mrow> <mo>Γ</mo> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math> dB, (<b>b</b>) <math display="inline"><semantics> <mrow> <mo>Γ</mo> <mo>=</mo> <mn>20</mn> </mrow> </semantics></math> dB.</p>
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<p>The transmit beam patterns obtained by P-RS-based and RS-based beamforming schemes with different numbers of users.</p>
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10 pages, 10160 KiB  
Article
Dual-Band Antenna Array Fed by Ridge Gap Waveguide with Dual-Periodic Interdigital-Pin Bed of Nails
by Boju Chen, Xiaoming Chen, Xin Cheng, Yiran Da, Xiaobo Liu, Steven Gao and Ahmed A. Kishk
Sensors 2024, 24(16), 5117; https://doi.org/10.3390/s24165117 - 7 Aug 2024
Viewed by 785
Abstract
A dual-band (K-/Ka-band) antenna array is presented. An ultra-wideband antenna element in the shape of a double-ridged waveguide is used as a radiation slot, and a novel dual-periodic ridge gap waveguide (RGW) with an interdigital-pin bed of nails (serving as a filter) is [...] Read more.
A dual-band (K-/Ka-band) antenna array is presented. An ultra-wideband antenna element in the shape of a double-ridged waveguide is used as a radiation slot, and a novel dual-periodic ridge gap waveguide (RGW) with an interdigital-pin bed of nails (serving as a filter) is used to realize dual-band operation. By periodically arranging the pins of two different heights in two dimensions, the proposed RGW with interdigital-pin bed of nails is able to realize and flexibly adjust two passbands. The widely used GW-based back cavity boosts the realized gain and simplifies the feed network design. A 4 × 4 prototype array was designed, fabricated, and measured. The results show that the array has two operating bands at 24.5–26.4 GHz and 30.3–31.5 GHz, and the realized gain can reach 19.2 dBi and 20.4 dBi, respectively. Meanwhile, there is a very significant gain attenuation at stopband. Full article
(This article belongs to the Special Issue Recent Trends and Developments in Antennas: Second Edition)
Show Figures

Figure 1

Figure 1
<p>Dual-periodic interdigital-pin GW unit cell with <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>3.2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>1.8</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1.6</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>p</mi> </msub> <mo>=</mo> <mi>g</mi> <mo>=</mo> <mn>1.2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>3.3</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>.</p>
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<p>Dispersion diagram of the unit cell given by <a href="#sensors-24-05117-f001" class="html-fig">Figure 1</a>.</p>
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<p>(<b>a</b>) Effect of <math display="inline"><semantics> <msub> <mi>d</mi> <mn>2</mn> </msub> </semantics></math> on the cutoff frequency of Mode 3 and Mode 4 with <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>p</mi> </msub> <mo>=</mo> <mi>g</mi> <mo>=</mo> <mn>1.2</mn> </mrow> </semantics></math> mm. (<b>b</b>) Effect of <math display="inline"><semantics> <msub> <mi>w</mi> <mi>p</mi> </msub> </semantics></math> on stop band with <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>1.8</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>.</p>
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<p>Dual-periodic interdigital-pin RGW with <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1.6</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>2.8</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>g</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>: (<b>a</b>) geometry and (<b>b</b>) simulated S-parameters.</p>
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<p>(<b>a</b>) Front view and (<b>b</b>) back view of the exploded proposed 2 × 2-element subarray.</p>
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<p>Geometries of the antenna parts: (<b>a</b>) radiating slots on the top layer; (<b>b</b>) top view of the cavity. (<b>c</b>) End of the ridge of the feed line (<math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>x</mi> </msub> <mo>=</mo> <mn>15.6</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>14</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mrow> <mi>s</mi> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>3</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mrow> <mi>s</mi> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>2.47</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mrow> <mi>s</mi> <mn>3</mn> </mrow> </msub> <mo>=</mo> <mn>4.68</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mrow> <mi>s</mi> <mn>4</mn> </mrow> </msub> <mo>=</mo> <mn>5</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>6.3</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mrow> <mi>r</mi> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mrow> <mi>r</mi> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>1.6</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>2.8</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>h</mi> <mi>s</mi> </msub> <mo>=</mo> <mn>1.75</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>r</mi> </msub> <mo>=</mo> <mn>2.3</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>1</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>2.3</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>6</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>c</mi> </msub> <mo>=</mo> <mn>2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>).</p>
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<p>Simulated reflection coefficients of the subarray with <math display="inline"><semantics> <mrow> <msub> <mi>d</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>3.2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math> and different <math display="inline"><semantics> <msub> <mi>d</mi> <mn>2</mn> </msub> </semantics></math>.</p>
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<p>Electric field distributions at the feed line at 25, 28, and 30.5 GHz.</p>
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<p>Configuration of the proposed array: (<b>a</b>) back view and (<b>b</b>) front view of the bottom layer; (<b>c</b>) back view and (<b>d</b>) front view of the middle layer; (<b>e</b>) the top layer.</p>
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<p>Photograph of the fabricated prototype: (<b>a</b>) front view (left) and back view (right) of each layer; (<b>b</b>) side view of the prototype with a waveguide-to-coaxial converter.</p>
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<p>Simulated and measured reflection coefficients of the prototype array.</p>
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<p>Simulated and measured radiation patterns at (<b>a</b>) 25 GHz in the E-plane, (<b>b</b>) 29 GHz (stopband) in the E-plane, (<b>c</b>) 31 GHz in the E-plane, (<b>d</b>) 25 GHz in the H-plane, (<b>e</b>) 29 GHz (stopband) in the H-plane and (<b>f</b>) 31 GHz in the H-plane. Solid lines represent co-polarization, dashed lines represent cross-polarization, red lines represent simulated results, and black lines represent measured results.</p>
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<p>(<b>a</b>) Simulated and measured realized gains of the prototype array. (<b>b</b>) Simulated and measured aperture efficiencies of the prototype array.</p>
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<p>Simulated reflection coefficient of the proposed array at different <math display="inline"><semantics> <msub> <mi>d</mi> <mn>2</mn> </msub> </semantics></math> when <math display="inline"><semantics> <mrow> <msub> <mi>w</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1.2</mn> <mspace width="4.pt"/> <mi>mm</mi> </mrow> </semantics></math>.</p>
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