Browsing by Author "Yalcinkaya, Bengisu"

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Low Signature UAVs: Radar Cross Section Analysis, Simulation, and Measurement in X-Band
(Springer London Ltd, 2025) Unalir, Dizdar; Yalcinkaya, Bengisu; Aydin, Elif; 06.03. Elektrik-Elektronik Mühendisliği; 06. Mühendislik Fakültesi; 01. Çankaya Üniversitesi
The increasing prevalence of unmanned aerial vehicles (UAVs) is driving the development of radar systems capable of detecting them. This hampers the deployment of UAVs in military operations. While radar cross section reduction (RCSR) can be a valuable solution, the research on this subject is inadequate. This paper presents an RCSR approach adopting a shaping technique for UAVs, demonstrating the proposed approach's efficacy through simulations and actual experimental measurements performed in X-Band on a four-legged UAV model. Using electromagnetic computational instruments, the shaping is applied to the designed UAV model with parameter-based simulations, the simulated radar cross section (RCS) values are derived, and the comparative analysis of these instruments is conducted. Experimental measurements are performed in laboratory conditions using a vector network analyzer. Actual measurement results are validated by simulative findings with the examination of the influence of frequency, polarization, and aspect angle on RCS. The demonstrated measuring approach allows cost-effective and easily applicable research on RCS in X-Band, a commonly utilized frequency range in military. An average RCSR of 10 dBsm has been accomplished with the presented shaping approach.
Citation - WoS: 1
Citation - Scopus: 1
Millimeter-Wave Sar Imaging for Sub-Millimeter Defect Detection With Non-Destructive Testing
(Mdpi, 2025) Yalcinkaya, Bengisu; Aydin, Elif; Kara, Ali; 06.03. Elektrik-Elektronik Mühendisliği; 06. Mühendislik Fakültesi; 01. Çankaya Üniversitesi
This paper introduces a high-resolution 77-81 GHz mmWave Synthetic Aperture Radar (SAR) imaging methodology integrating low-cost hardware with modified radar signal characteristics specifically for NDT applications. The system is optimized to detect minimal defects in materials, including low-reflectivity ones. In contrast to the existing studies, by optimizing key system parameters, including frequency slope, sampling interval, and scanning aperture, high-resolution SAR images are achieved with reduced computational complexity and storage requirements. The experiments demonstrate the effectiveness of the system in detecting optically undetectable minimal surface defects down to 0.4 mm, such as bonded adhesive lines on low-reflectivity materials with 2500 measurement points and sub-millimeter features on metallic targets at a distance of 30 cm. The results show that the proposed system achieves comparable or superior image quality to existing high-cost setups while requiring fewer data points and simpler signal processing. Low-cost, low-complexity, and easy-to-build mmWave SAR imaging is constructed for high-resolution SAR imagery of targets with a focus on detecting defects in low-reflectivity materials. This approach has significant potential for practical NDT applications with a unique emphasis on scalability, cost-effectiveness, and enhanced performance on low-reflectivity materials for industries such as manufacturing, civil engineering, and 3D printing.
Model Enhancement for UAV Stealth in X-Band
(Institute of Electrical and Electronics Engineers Inc., 2025) Unalir, Dizdar; Yalcinkaya, Bengisu; Aydin, Elif; 06.03. Elektrik-Elektronik Mühendisliği; 06. Mühendislik Fakültesi; 01. Çankaya Üniversitesi
With the rapid advancement of technology, radar detection techniques continue to evolve, challenging the effectiveness of traditional unmanned aerial vehicles (UAVs) stealth techniques. As the usage of UAVs in military applications expands, the need for effective radar cross section reduction (RCSR) methods to enhance their stealth capabilities has grown significantly. In this study, we propose an enhancement of a previously developed Low-RCS UAV model, focusing on RCSR with shaping technique in the X-band. For the identification and optimization of the UAV model’s highly reflective components, a detailed simulative analysis of the RCS was performed using CST Studio Suite Environment. The modifications are applied to the body and leg components to minimize radar reflections. Simulation results demonstrated that the proposed enhancements significantly reduced RCS values compared to the original Low-RCS UAV model. A total of 13 dBsm reduction in RCS was observed compared to the traditional UAV models. Comparative analysis for different frequencies in X-Band and various aspect angles confirmed the effectiveness of the improved design, validating its potential for stealth applications. The findings can contribute to the research in UAV stealth technology and provide insights into future low-visibility UAV designs. © 2025 Elsevier B.V., All rights reserved.