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Conference Object Model Enhancement for UAV Stealth in X-Band(IEEE, 2025) Unalir, Dizdar; Yalcinkaya, Bengisu; Aydin, ElifWith 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.Conference Object Citation - WoS: 4Citation - Scopus: 6A Reinforcement Learning Algorithm for Data Collection in Uav-Aided Iot Networks With Uncertain Time Windows(Ieee, 2021) Cicek, Cihan TugrulUnmanned aerial vehicles (UAVs) have been considered as an efficient solution to collect data from ground sensor nodes in Internet-of-Things (IoT) networks due to their several advantages such as flexibility, quick deployment and maneuverability. Studies on this subject have been mainly focused on problems where limited UAV battery is introduced as a tight constraint that shortens the mission time in the models, which significantly undervalues the UAV potential. Moreover, the sensors in the network are typically assumed to have deterministic working times during which the data is uploaded. In this study, we revisit the UAV trajectory planning problem with a different approach and revise the battery constraint by allowing UAVs to swap their batteries at fixed stations and continue their data collection task, hence, the planning horizon can be extended. In particular, we develop a discrete time Markov process (DTMP) in which the UAV trajectory and battery swapping times are jointly determined to minimize the total data loss in the network, where the sensors have uncertain time windows for uploading. Due to the so-called curse-of-dimensionality, we propose a reinforcement learning (RL) algorithm in which the UAV is trained as an agent to explore the network. The computational study shows that our proposed algorithm outperforms two benchmark approaches and achieves significant reduction in data loss.Conference Object Citation - Scopus: 2Miniaturized 2.4 Ghz Antenna Design for Uav Communication Link;(Institute of Electrical and Electronics Engineers Inc., 2020) Yilmaz,V.S.; Kara,A.; Aydin,E.In many communications applications, unlike conventional antennas, lightweight, flexible, small antennas that can adapt to mechanical and industrial constraints are required. In this study, the results of antenna design operating at 2.4 GHz are presented for use in Unmanned Aerial Vehicle (UAV) tele command links. In the parametric and optimization studies carried out on the antenna, it is aimed to increase the gain while keeping the size as small as possible. The requirements of the industry, such as light, aesthetics, miniature and high gain aspects of the antenna were targeted in the design process. Finally, an antenna of 55.2x88 mm size and 7dB gain was achieved using commercial electromagnetic design tools. The designed antenna become satisfying industrial requirements with these features. © 2020 IEEE.Article Citation - WoS: 32Citation - Scopus: 39Backhaul-Aware Optimization of Uav Base Station Location and Bandwidth Allocation for Profit Maximization(Ieee-inst Electrical Electronics Engineers inc, 2020) Cicek, Cihan Tugrul; Gultekin, Hakan; Tavli, Bulent; Yanikomeroglu, HalimUnmanned Aerial Vehicle Base Stations (UAV-BSs) are envisioned to be an integral component of the next generation Wireless Communications Networks (WCNs) with a potential to create opportunities for enhancing the capacity of the network by dynamically moving the supply towards the demand while facilitating the services that cannot be provided via other means efficiently. A significant drawback of the state-of-the-art have been designing a WCN in which the service-oriented performance measures (e.g., throughput) are optimized without considering different relevant decisions such as determining the location and allocating the resources, jointly. In this study, we address the UAV-BS location and bandwidth allocation problems together to optimize the total network profit. In particular, a Mixed-Integer Non-Linear Programming (MINLP) formulation is developed, in which the location of a single UAV-BS and bandwidth allocations to users are jointly determined. The objective is to maximize the total profit without exceeding the backhaul and access capacities. The profit gained from a specific user is assumed to be a piecewise-linear function of the provided data rate level, where higher data rate levels would yield higher profit. Due to high complexity of the MINLP, we propose an efficient heuristic algorithm with lower computational complexity. We show that, when the UAV-BS location is determined, the resource allocation problem can be reduced to a Multidimensional Binary Knapsack Problem (MBKP), which can be solved in pseudo-polynomial time. To exploit this structure, the optimal bandwidth allocations are determined by solving several MBKPs in a search algorithm. We test the performance of our algorithm with two heuristics and with the MINLP model solved by a commercial solver. Our numerical results show that the proposed algorithm outperforms the alternative solution approaches and would be a promising tool to improve the total network profit.Conference Object Citation - WoS: 2Citation - Scopus: 2Radar Cross Section Studies of Low Signature UAVs in X-Band: Simulation, Measurement and Performance Evaluation(IEEE, 2024) Unalir, Dizdar; Gokdogan, Bengisu Yalcinkaya; Aydin, ElifIn this study, the effectiveness of a radar cross section (RCS) reduction method based on a proposed shaping technique for four-legged unmanned aerial vehicles (UAV) has been proven with simulation tools and experimental measurements in X-Band. Simulative RCS values were obtained with CST and HFSS electromagnetic calculation tools, and the advantages of these tools compared to each other were examined. Experimental measurements were carried out in a laboratory environment with a vector network analyzer (VNA) and confirmed with simulation results. The effects of frequency, polarization and aspect angle factors on RCS were examined. It has been shown that with the proposed measurement method, low-cost and easily applicable RCS analysis can be performed in X-Band, one of the frequency bands frequently used in the defense industry. With the proposed shaping method, RCS reduction in the range of 5-10 dBsm was achieved.Conference Object Citation - WoS: 2Citation - Scopus: 5Low Radar Cross Section Uav Design in X-Band(Ieee, 2022) Unalir, Dizdar; Sezgin, Sila; Yuva, Cansu Sena; Yalcinkaya Gokdogan, Bengisu; Aydin, ElifAs Unmanned Aerial Vehicles (UAVs) have become widespread in defense industry, the radar technology that can detect them has also improved. These improvements cause UAVs to be detected more easily, which limits their effectiveness in military usage. Although the reduction of the radar cross-section (RCS) can provide a solution to this issue, the studies regarding that is insufficient in the literature. In this study, a shaping method is recommended to reduce the RCS of UAVs, and it is shown the method is effective to address the problem. Firstly, using a simulation tool, an UAV model is designed from simple shapes and the model is validated by comparing it with the ones in literature. Secondly, RCS values are measured using vertical and horizontal polarization throughout 360 degrees by incrementing the aspect angle by one degree in X-Band using the CST Studio Suite environment. Then, considering the hardware and aerodynamic requirements as well as limitations of the UAV model, a shaping technique is applied to the body, legs and the hollow parts of the UAV model with parametric simulations. The results show that the recommended shaping technique can provide a significant reduction in the RCS of an UAV.
