Ic-Pyo Hong

Reconfigurable intelligent surfaces (RISs) require joint choices of tuning element, addressing, tolerance, and calibration. This paper presents a conditional co-design framework evaluated analytically and through reproducible numerical experiments. A perimeter-capacity ratio screens specified edge-escape architectures while distinguishing external wiring from independent per-cell control. Its illustrative one-square-meter boundary depends on line multiplicity, routing pitch, and usable layers and does not prove PCB unroutability. A coupled tolerance study compares ensemble variance, realization RMS, and piston/tilt-removed RMS. Spatial structure changes sidelobes and pointing, while apparent peak-gain recovery with correlation partly depends on normalization. Scan-specific checks correct a phase-datum sensitivity in two-bit quantization. A balanced four-phase power protocol separates complex state contrasts from an anchored physical cell lookup table. Decision-margin tests replace a universal coupling threshold; joint noise and multipath experiments state the reference, rank, and stationarity conditions. Short delay-line cells are distinguished from full-aperture true-time-delay control. A revised 28 GHz architecture comparison includes serial per-cell storage, uncertainty intervals, and requirement sensitivity. Multiple candidates satisfy the pattern, latency, and perimeter screens under stated command laws; physical stack-up, non-linear tuning, and stationarity still require hardware-specific verification. The framework supports traceable design comparisons rather than universal frequency, resolution, or manufacturing limits.

In this paper, an energy-selective surface (ESS) structure operating at 3.5 GHz is designed to protect various communication systems from high-power microwave (HPM) threats. The proposed structure achieves wideband blocking characteristics by stacking a grid pattern with a cross-shaped patch pattern. Simulation results show that the ESS structures provide a pass bandwidth of 1.47 GHz based on a -2 dB at low-power signal and a wideband blocking bandwidth of 15 GHz based on a -15 dB at high-power signal. The proposed unit structure was validated by measuring the received signal strength according to change in incident wave intensity using a waveguide measurement setup. The measurement results confirm that the shielding effectiveness increases when the incident power exceeds 21 dBm. It was confirmed that the proposed ESS structures can actively block high-power signals.

Despite the rapid expansion of unmanned aerial vehicle (UAV) applications across precision agriculture, logistics, infrastructure inspection, disaster response, and aerial surveying, objective and quantitative hardware evaluation criteria for UAV components remain insufficiently developed. This paper proposes quantitative key performance indicators (KPIs) for thirteen core hardware subsystems, including airframe and propulsion, battery and power supply, flight control, wireless communication, imaging (camera), Global Positioning System (GPS)/Global Navigation Satellite System (GNSS) positioning, thermal management, acoustic and vibration characteristics, AI-based autonomous flight, electromagnetic compatibility (EMC), cybersecurity, and reliability and environmental qualification, together with LiDAR payload evaluation criteria. International standardization activities by 3GPP (Release 15/17), IEEE (1936–1958 series), American society for photogrammetry and remote sensing (ASPRS), and national regulatory frameworks are synthesized to define measurable performance metrics and recommended test methods for each subsystem. An integrated KPI matrix maps application-domain-specific performance targets—encompassing surveying (real-time kinematic (RTK) horizontal accuracy ≤ 2 cm root-mean-square error (RMSE), ground sample distance (GSD) ≤ 2 cm/px), infrastructure inspection (LiDAR payload up to 8 kg, beyond visual line-of-sight (BVLOS) latency ≤ 140 ms), and logistics delivery (payload ≥ 2 kg, precision landing ≤ 50 cm)—demonstrating that no universal platform can simultaneously satisfy all domain requirements. A fuzzy-AHP weighting procedure and inter-subsystem coupling analysis are introduced to address size, weight, and power (SWaP) trade-off relationships that purely additive scoring models cannot capture. The proposed evaluation framework is intended to contribute practically to UAV standardization, certification, and quality management across the full design–procurement–operation lifecycle.

This work presents a generative machine learning model that predicts upper graphene element configurations for a multilayer flexible electromagnetic absorber. The model uses the lower graphene layer as input and S-parameters as conditional input. It is increasingly difficult to fabricate multilayer absorbers using the conventional design process, which introduces performance and efficiency issues. With advances in machine learning algorithms and corresponding hardware, it is becoming easier to design multilayer absorbers using machine learning approaches. A conditional variational autoencoder—a type of generative machine learning model—was used to train our model. We integrated a residual network into our encoder portion to enable better feature extraction capabilities for our proposed model. We prepared the dataset using the High Frequency Structure Simulator, an electromagnetic simulation software program developed by Ansys. We reconstructed the upper and lower graphene structures from the dataset and predicted the upper graphene structure using the given S-parameters and the lower graphene structure of the absorber. Satisfactory agreement between the predicted and actual structures was observed.

Short-range three-dimensional (3D) synthetic aperture radar (SAR) imaging has drawn significant attention across various domains, including security surveillance, non-destructive testing, and medical diagnostics. This paper introduces a fast adaptive alternative direction method of multipliers (FA-ADMM) framework designed to enhance both efficiency and accuracy in SAR image reconstruction. Our approach addresses two key challenges in the single holographic frequency ADMM (SFH-ADMM) model: image degradation from fast Fourier transform operations and slow convergence due to fixed ADMM penalty parameters. To overcome these issues, we refine the augmented Lagrangian formulation to ensure stable convergence and introduce an adaptive tuning mechanism that dynamically adjusts penalty parameters based on the connection between relaxed ADMM and relaxed Douglas–Rachford splitting. Additionally, we seamlessly integrate denoising convolutional neural network and autoencoder architectures into the iterative process to enhance noise suppression and image fidelity, respectively. The synergy of these innovations within a unified framework significantly accelerates convergence and improves reconstruction quality, making it well suited for real-world short-range 3D SAR applications.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

Ship detection through synthetic aperture radar (SAR) imagery is essential for maritime monitoring, security, and navigation. However, SAR images present several challenges, including noise, low contrast, and varying ship sizes. In this paper, we propose an architecture that incorporates ResNet-50 as the backbone for multi-scale feature extraction, which is further enhanced using a convolutional block attention module for refining spatial and channel-wise features. Feature combination and attention fusion mechanisms are employed to integrate critical features while suppressing irrelevant information, and detection heads are optimized for precise bounding box regression and classification. This design ensures improved efficiency and accuracy, demonstrating significant advancements in SAR ship detection performance. Extensive experiments conducted on the SAR ship detection dataset and the high-resolution SAR image dataset yielded AP50 scores of 98.1% and 91.8%, respectively, outperforming several state-of-the-art detectors, thus validating the effectiveness of the proposed method.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)