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Article ISAR Imaging of Drone Swarms at 77 GHz(Tubitak Scientific & Technological Research Council Turkey, 2025) Coruk, Remziye Busra; Kara, Ali; Aydin, ElifThe proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense antidrone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, sizes, and payload configurations by employing ANSYS simulations. To enhance image quality, different window functions are evaluated, and the Hamming window is selected due to its highest peak signal-to-noise ratio (PSNR) (16.3645) and structural similarity (SSIM) (0.9067) values, ensuring superior noise reduction and structural preservation. The results demonstrate that the effectiveness of high-resolution ISAR imaging in accurately detecting and characterizing drone swarms pave the way for enhanced airspace security measures.Article Citation - WoS: 10Citation - Scopus: 15An Rfid Based Indoor Tracking Method for Navigating Visually Impaired People(Tubitak Scientific & Technological Research Council Turkey, 2010) Oktem, Rusen; Aydin, ElifThis paper tackles the RFID based tracking problem in an obscured indoor environment. The proposed solution is an integral part of a navigation aid for guiding visually impaired people in a store. It uses RF signal strengths and is based on the Bayes Decision Theory. An observation vector is formed by received radio signal strength indication values, transmitted from three transmitters at distinct frequencies in the UHF band. The indoor area is divided into square grids, where each grid is considered as a class. The problem of tracking is expressed as classifying the observed radio signal strengths to the most likely class. A classification rule is formulated by incorporating a priori assumptions appropriate for the studied model. The proposed approach is tested in a laboratory environment. The results prove that the proposed approach is promising in tracking especially when the tracked person is guided by a system.
