Search Results (1,063)

This paper presents an innovative end-to-end framework for conformal antenna array design and beam steering in Low Earth Orbit (LEO) satellite-based IoT communication systems. We propose a multi-stage learning architecture that integrates machine learning (ML) for antenna parameter prediction with reinforcement learning (RL) for adaptive beam steering. The ML module predicts optimal geometric and material parameters for conformal antenna arrays based on mission-specific performance requirements such as frequency, gain, coverage angle, and satellite constraints with an accuracy of 99%. These predictions are then passed to a Deep Q-Network (DQN)-based offline RL model, which learns beamforming strategies to maximize gain toward dynamic ground terminals, without requiring real-time interaction. To enable this, a synthetic dataset grounded in statistical principles and a static dataset is generated using CST Studio Suite and COMSOL Multiphysics simulations, capturing the electromagnetic behavior of various conformal geometries. The results from both the machine learning and reinforcement learning models show that the predicted antenna designs and beam steering angles closely align with simulation benchmarks. Our approach demonstrates the potential of combining data-driven ensemble models with offline reinforcement learning for scalable, efficient, and autonomous antenna synthesis in resource-constrained space environments. Full article

This paper presents a multi-problem surrogate-assisted evolutionary multi-objective optimization approach for antenna design. By transforming the traditional antenna design optimization problem into expensive multi-objective optimization problems, this method employs a multi-problem surrogate (MPS) model to stack multiple antenna design problems. The MPS model is a knowledge-transfer framework that stacks multiple surrogate models (e.g., Gaussian Processes) trained on related antenna design problems (e.g., Yagi–Uda antennas with varying director configurations) to accelerate optimization. The parameters of Yagi–Uda antenna including radiation patterns and beamwidth—across various director configurations are considered as decision variables. The several surrogates are constructed based on the number of directors of Yagi–Uda antenna. The MPS algorithm identifies promising candidate solutions using an expected improvement strategy and refines them through true function evaluations, effectively balancing exploration with computational cost. Compared to benchmark algorithms assessed by hypervolume, our approach demonstrated superior average performance while requiring fewer function evaluations. Full article

Deeply implanted biomedical devices like leadless pacemakers require an antenna with minimal volume and high radiation efficiency to ensure reliable in-body communication and long operational time within the human body. This paper introduces a novel implantable antenna designed to significantly reduce the spatial requirements within an implantable capsule while maintaining high radiation efficiency in lossy media like heart tissue. The design principles of the proposed antenna are outlined, followed by antenna parameters and an equivalent circuit study that demonstrates how to fine-tune the antenna’s resonant frequency. The radiation characteristics of the antenna are thoroughly investigated, revealing a radiation efficiency of up to 28% at the Medical Implant Communication System (MICS) band and 56% at the 2.4 GHz ISM band. The transmission efficiency between two deeply implanted antennas within heart tissue has been improved by more than 15 dB compared to the current state of the art. The radiation and transmission performance of the proposed antennas has been validated through comprehensive simulations using anatomical human body models, phantom measurements, and in vivo animal experiments, confirming their superior radiation performance. Full article

This paper presents an intelligent design framework for a high-performance 26 GHz MIMO antenna array tailored to 5G applications, built upon a compact single-element patch. The 11.5 mm × 11.5 mm × 1.6 mm microstrip patch on FR4 exhibits near-unity electrical length, an ultra-deep return loss (S11 < −40 dB at 26 GHz), and a wide operational bandwidth from 24.4 to 31.2 GHz (6.8 GHz, ~26.2%). A two-element array, spaced at λ/2, is first augmented with a inspired metamaterial (MTM) unit cell whose dimensions are optimized via a Multi-Layer Perceptron (MLP) model to maximize gain (+2 dB) while preserving S11. In the second phase, a closed-square parasitic ring is introduced between the elements; its side length, thickness, and position are predicted by a Random Forest (RF) model with Bayesian optimization to minimize mutual coupling (S12) from −25 dB to −58 dB at 26 GHz without significantly degrading S11 (remains below −25 dB). Full-wave simulations and anechoic chamber measurements confirm the ML predictions. The close agreement among predicted, simulated, and measured S-parameters validates the efficacy of the proposed AI-assisted optimization methodology, offering a rapid and reliable route to next-generation millimeter-wave MIMO antenna systems. Full article

This study addresses the key technical challenges in monitoring hydraulic fracturing within unconventional reservoirs through an innovative wide-field electromagnetic (WEM) monitoring technique. The method employs a 5A AC-excited wellbore-fracturing fluid system to establish a conductor antenna effect, coupled with a surface electrode array (100–250 m offset) to detect millivolt-level time-lapse potential anomalies, enabling real-time dynamic monitoring of 142 fracturing stages. A line current source integral model was developed to achieve quantitative fracture network inversion with less than 12% error, attaining 10 m spatial resolution and dynamic updates every 10 min (80% faster than conventional methods). Optimal engineering parameters were identified, including fluid intensity ranges of 25–30 m³/m for tight sandstone and 30–35 m³/m for shale, with particulate diverters achieving 93.1% diversion efficiency (significantly outperforming chemical diverters at 35%). Application in deep reservoirs maintained signal attenuation rates below 5% per kilometer. Theoretically, a nonlinear relationship model between fluid intensity and stimulated area was established, while practical implementation through real-time adjustments in 142 stages enhanced single-well production by 15–20% and reduced diverter costs, advancing the paradigm shift from empirical to scientific fracturing in unconventional reservoir development. Full article

Kapton and Mylar film materials are used to manufacture space inflatable antenna reflectors; therefore, their mechanical characteristics are considered important parameters for the design of inflatable antenna reflectors. This paper mainly introduces a series of experiments on the mechanical properties of Kapton VN and Kapton HN, and Mylar I and II film specimens, including film tensile tests, film seam tests with tape bonding and glue bonding, and skirt edge joint tests. Therefore, failure modes, stress versus strain curves, ultimate tensile strength, and extension at break are obtained for these specimens of Kapton VN and Kapton HN and Mylar I and II films. Based on these measured data, stress conditions of models with 12 and 18 sections using ANASYS are compared to identify the effect of different sections and pressures on the force of inflatable antenna reflectors. Full article

Novel K band wearable sensors and antennas for Telemonitoring, Telehealth and Telemedicine Systems, Internet of Things (IoT) systems, and communication sensors are discussed in this paper. Only in a limited number of papers are K band sensors presented. One of the major goals in the evaluation of Telehealth and Telemedicine and wireless communication devices is the development of efficient compact low-cost antennas and sensors. The development of wideband efficient antennas is crucial to the evaluation of wideband and multiband efficient Telemonitoring, Telehealth and Telemedicine wearable devices. The advantage of the printed wearable antenna is that the feed and matching network can be etched on the same substrate as the printed radiating antenna. K band slot antennas and arrays are presented in this paper the sensors are compact, lightweight, efficient, and wideband. The antennas’ design parameters, and comparison between computation and measured electrical performance of the antennas, are presented in this paper. Fractal efficient antennas and sensors were evaluated to maximize the electrical characteristics of the communication and medical devices. This paper presents wideband printed antennas in frequencies from 16 GH to 26 GHz for Telemonitoring, Telehealth and Telemedicine Systems. The bandwidth of the K band fractal slot antennas and arrays ranges from 10% to 40%. The electrical characteristics of the new compact antennas in the vicinity of the patient body were measured and simulated by using electromagnetic simulation techniques. The gain of the new K band fractal antennas and slot arrays presented in this paper ranges from 3 dBi to 7.5 dBi with 90% efficiency. Full article

Sparse arrays can effectively reduce antenna cost and implementation complexity. However, most existing research in sparse array design mainly focuses on far-field scenarios, which cannot be directly applied to near-field (NF) source localization, where the delay term and source incident parameters exhibit a nonlinear relationship. In this paper, employing a symmetric enhanced nested array, a high-precision underdetermined three-dimensional (3D) NF localization method is proposed. Firstly, the symmetry of the array and the fourth-order cumulant are utilized to construct the equivalent virtual far-field (FF) received data. Then, a gridless, sparse, and parametric approach combined with an l₁-singular value decomposition-based pairing procedure is employed to obtain estimates of two paired angles. Finally, a one-dimensional (1D) spectral estimator is applied to obtain the estimate of the range parameter. By analyzing the virtual aperture, the optimal parameter configuration for a given number of elements is obtained. As shown by simulation results, the proposed method can handle underdetermined estimation. Compared with the other algorithms, the proposed algorithm achieves significant improvements in both angular and distance accuracy, with enhancements of 65% and 61.7%, respectively. Full article

With the increasing deployment of unmanned surface vessels (USVs) in complex marine operations such as ocean monitoring, search and rescue, and military reconnaissance, precise heading control under environmental disturbances and system delays has become a critical challenge. This paper presents an advanced robust heading control strategy for USVs operating under these demanding conditions. The proposed approach integrates three key innovations: (1) an enhanced Smith predictor for accurate time-delay compensation, (2) a variable-universe fuzzy PID controller with self-adaptive scaling domains that dynamically adjust to error magnitude and rate of change, and (3) a hybrid metaheuristic optimization algorithm combining beetle antennae search, harmony search, and genetic algorithm (BAS-HSA-GA) for optimal parameter tuning. Through comprehensive simulations using a Nomoto first-order time-delay model under combined white noise and second-order wave disturbances, the system demonstrates superior performance with over 90% reduction in steady-state heading error and ≈30% faster settling time compared to conventional PID and single-optimization fuzzy PID methods. Field trials under sea-state 4 conditions confirm 15–25% lower tracking error in realistic operating scenarios. The controller’s stability is rigorously verified through Lyapunov analysis, while comparative studies show significant improvements in S-shaped path tracking performance, achieving better IAE/ITAE metrics than DRL, ANFC, and ACO approaches. This work provides a comprehensive solution for high-precision, delay-resilient USV heading control in dynamic marine environments. Full article

With the continuous advancement of on-orbit services and space intelligence sensing technologies, the efficient and accurate identification of spacecraft components has become increasingly critical. However, complex lighting conditions, background interference, and limited onboard computing resources present significant challenges to existing segmentation algorithms. To address these challenges, this paper proposes a lightweight spacecraft component segmentation framework for on-orbit applications, termed M4MLF-YOLO. Based on the YOLOv5 architecture, we propose a refined lightweight design strategy that aims to balance segmentation accuracy and resource consumption in satellite-based scenarios. MobileNetV4 is adopted as the backbone network to minimize computational overhead. Additionally, a Multi-Scale Fourier Adaptive Calibration Module (MFAC) is designed to enhance multi-scale feature modeling and boundary discrimination capabilities in the frequency domain. We also introduce a Linear Deformable Convolution (LDConv) to explicitly control the spatial sampling span and distribution of the convolution kernel, thereby linearly adjusting the receptive field coverage range to improve feature extraction capabilities while effectively reducing computational costs. Furthermore, the efficient C3-Faster module is integrated to enhance channel interaction and feature fusion efficiency. A high-quality spacecraft image dataset, comprising both real and synthetic images, was constructed, covering various backgrounds and component types, including solar panels, antennas, payload instruments, thrusters, and optical payloads. Environment-aware preprocessing and enhancement strategies were applied to improve model robustness. Experimental results demonstrate that M4MLF-YOLO achieves excellent segmentation performance while maintaining low model complexity, with precision reaching 95.1% and recall reaching 88.3%, representing improvements of 1.9% and 3.9% over YOLOv5s, respectively. The mAP@0.5 also reached 93.4%. In terms of lightweight design, the model parameter count and computational complexity were reduced by 36.5% and 24.6%, respectively. These results validate that the proposed method significantly enhances deployment efficiency while preserving segmentation accuracy, showcasing promising potential for satellite-based visual perception applications. Full article

In LEO constellation–augmented navigation, the transmitting antenna phase center offset (PCO) and the equipment delay associated with the downlink signals of LEO satellites constitute major error sources that must be precisely characterized. Previous studies primarily focused on single or small-scale satellite scenarios, lacking comprehensive evaluations regarding the influence of constellation scale, orbital altitude, ground station configuration, and various error sources. To address this gap, we propose a joint estimation method utilizing observations from a limited number of regional ground stations in China that simultaneously track GNSS and LEO satellites. The method is specifically designed to accommodate practical constraints on ground station distribution within China. Initially, a batch least-squares estimation strategy is employed to simultaneously determine the ionosphere-free PCO and initial equipment delays for all LEO satellites in a constellation-wide solution. Subsequently, the estimated PCO parameters are fixed, and the equipment delays are further refined using a precise point positioning (PPP) approach. To systematically evaluate the method’s performance under realistic conditions, we analyze the impact of orbital altitude, constellation size, ground station number, data processing duration, and orbit/clock biases through comprehensive simulations. The results indicate: (1) the Z-direction component of the PCO (pointing toward the Earth’s center) and equipment delay is more sensitive to orbit and clock errors; (2) Increasing the number of LEO satellites generally improves the estimation accuracy of equipment delays, but the marginal gain diminishes as the constellation size expands; (3) sub-centimeter PCO accuracy and equipment delay accuracies better than 3 cm can still be achieved using only 3–4 regionally distributed ground stations over an observation period of 5–7 days. Full article

This paper presents the design of a circularly polarized RFID ground mat antenna for UHF-band sports-event applications. Considering a practical sports-event timing system, the ground-based mat antenna with characteristics of a low-backward radiation and circular polarization is proposed. A multilayer square patch antenna using an acrylic dielectric substrate with a wideband branch-line coupler feeding network is employed to improve overall radiation efficiency, which, in turn, provides two excitation port with a phase difference of 90°. Thus, right-hand circular polarization can be obtained. Instead of a conventional FR4–air–FR4 structure, the proposed FR4–acrylic–FR4 composite configuration is adopted to substantially increase the antenna’s mechanical strength and durability against external pressure from runners. The antenna’s performance is attributed to the use of an effective composite dielectric constant and an optimized design of its parameters. Additionally, the patch antenna’s low-backward radiation characteristic helps reduce multipath interference in real-world applications. The measured results are in good agreement with the simulated data, validating the proposed antenna design. In order to further assess the practical performance of the antenna, outdoor measurements are carried out to validate the estimated reading distances derived from controlled anechoic chamber tests. The measured return loss remained below −10 dB across the frequency range of 755–990 MHz, exhibiting a slight discrepancy compared to the simulated bandwidth of 800–1030 MHz. For the characteristic of the circular polarization, the measured axial ratio is below 3 dB within the range of 860–920 MHz. While a more relaxed criterion of an axial ratio below 6 dB is considered, the operating frequency range extends from 560 MHz to 985 MHz, which falls within the frequency band relevant for RFID reader applications. Full article

The rapid growth of wireless communication demands has led to heightened competition for limited spectrum resources, with traditional allocation methods proving insufficient to meet evolving needs. In response, DSA has emerged as a promising strategy, allowing secondary users to access underutilised portions of the spectrum, particularly in bands primarily allocated for satellite communication, such as the 3.4–4.2 GHz range. DSA offers a flexible solution by enabling the secondary use of the underutilised spectrum while protecting primary users like terrestrial FSS/SS. This paper surveys state-of-the-art DSA techniques and introduces the concept of DSUE to quantify real-time spectrum reuse effectiveness under coexistence constraints. Emphasis is placed on integrating FSS ground station parameters—such as location, antenna orientation, and sensitivity—into intelligent spectrum management frameworks. The review also evaluates ML/AI-driven resource allocation and interference mitigation approaches that enhance coexistence performance. By structuring a DSUE-aware environment, this study provides technical direction for harmonising terrestrial wireless mobile broadband and satellite systems, enabling more efficient, adaptive, and interference-aware spectrum sharing. Full article

This paper discusses the design, manufacturing, and experimental characterization of a Ka-band fully dielectric reflectarray realized using Zetamix $\epsilon$ 7.5 ceramic material and additive manufacturing. Properly tuning the infill during the manufacturing process, it is possible to control the permittivity of the material, which can therefore be considered, to all intents and purposes, an additional degree of freedom for optimizing the unit cell and consequently the reflectarray performance. The optimal values of ${\epsilon }_r$ are determined through numerical analysis of the unit cell and experimental characterization of bricks manufactured with different printing parameters. Then, the unit cell is used to design a medium-sized reflectarray with an aperture of 207.4${\lambda }_0^2$ and a thickness of 0.44${\lambda }_0$, at the design frequency $f_0=30$ GHz. The full-wave simulations of the designed RA and experimental measurements of a prototype confirm the excellent performance of the antenna, which exhibits a broadband flat response from 28 to 31 GHz and an aperture efficiency exceeding 50%. Full article

Objective: Microwave hyperthermia is a clinically validated adjunctive therapy in oncology, employing antenna applicators to selectively raise tumor tissue temperature to 40–44 °C. For deep-seated tumors, especially those in anatomically complex areas like the head and neck (H&N) region, phased array antennas are typically employed. Determining optimal antenna feeding coefficients is crucial to maximize the specific absorption rate (SAR) within the tumor and minimize hotspots in healthy tissues. Conventionally, this optimization relies on meta-heuristic global algorithms such as particle swarm optimization (PSO). Methods: In this study, we consider a deterministic alternative to PSO in microwave hyperthermia SAR-based optimization, which is based on the Alternating Projections Algorithm (APA). This method iteratively projects the electric field distribution onto a set of constraints to shape the power deposition within a predefined mask, enforcing SAR focusing within the tumor while actively suppressing deposition in healthy tissues. To address the challenge of selecting appropriate power levels, we introduce an adaptive power threshold search mechanism using a properly defined quality parameter, which quantifies the excess of deposited power in healthy tissues. Results: The proposed method is validated on both a simplified numerical testbed and a realistic anatomical phantom. Results demonstrate that the proposed method achieves heating quality comparable to PSO in terms of tumor targeting, while significantly improving hotspot suppression. Conclusions: The proposed APA framework offers a fast and effective deterministic alternative to meta-heuristic methods, enabling SAR-based optimization in microwave hyperthermia with improved tumor targeting and enhanced suppression of hotspots in healthy tissue. Full article