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  • Publication
    Characterizing Attenuation of Bumper Modifications: A Comparative Study in the E-Band
    (IEEE, 2024) Neubauer, Michael; Hirschmugl, Michael; Petanjek, David; Kiebach, Helge; Karamzadeh, Saeid; Kolosovs, D; Anstalt fur Verbrennungskraftmaschinen List; Bahcesehir University
    Having knowledge about the attenuation of the materials surrounding a radar sensor is of great importance in the automotive sector. Only then can the manufacturer guarantee the desired functionality of the sensor. Due to the fact that a lot of automotive manufacturers also started integrating radar sensors behind rear bumpers for improved visibility to the back of a car, it is vital to know how those bumpers and possible repair scenarios done to them can affect the radar sensor. This paper proposes a way to measure the attenuation in the E-band of not only square slab samples representing various types of paint and repair scenarios on automotive bumpers, but also actual rear bumpers with different types of repair scenarios. The results are then presented and compared relative to each other.
  • Publication
    Neural Network-Based Human Detection Using Raw UWB Radar Data
    (IEEE, 2024) Dogan, Emine Berjin; Yousefi, Mohammad; Soyak, Ece Gelal; Karamzadeh, Saeid; Kolosovs, D; Bahcesehir University; Bahcesehir University; Bahcesehir University; Bahcesehir University
    Ultra-Wideband (UWB) radar technology is a widely used technology for human detection and tracking through walls, because of its effectiveness in low-visibility situations. This study demonstrates a neural network-based identification of human presence using raw data obtained directly from the UWB radar. First, measurements have been collected with different human subjects at different positions relative to the UWB radar. A convolutional neural network (CNN) model has been trained on this dataset, to detect the presence of a human. Next, the algorithm effectiveness is deeply investigated using the Gradient-weighted Class Activation Mapping (Grad-CAM) method, and the observations on detected presence are discussed.
  • Publication
    Evaluating Substrate Influence on Rectangular and Circular Microstrip Patch Antennas for 5G
    (IEEE, 2024) Goksel, Fatih; Karamzadeh, Saeid; Kolosovs, D; Bahcesehir University; Bahcesehir University
    Microstrip Patch Antennas (MSPAs) are favored for their low production cost, compact size, lightweight nature, and adaptability to planar and non-planar surfaces. They are particularly suitable for wideband and multi-frequency operations, making them ideal for sub-6 GHz applications in 5G devices. This study aims to design and compare rectangular and circular MSPAs using six different substrates: FR4 Glass Epoxy (dielectric constant 4.3), ROGERS DT5880 (2.2), ROGERS 4003C (3.3), Teflon (2.1), Arlon AD300A (3), and Alumina (9.9). Using CST Microwave Studio, we first design rectangular MSPAs and then circular MSPAs, maintaining a 1.6 mm substrate height and using Copper (Anneal) for both the patch and ground materials. The target frequency is 5.8 GHz, relevant for 5G applications. By comparing the antenna parameters across different substrates, we aim to identify the optimal substrate and antenna design for future technology needs.
  • Publication
    The artifacts of human physical motions on vital signs monitoring
    (IEEE, 2019) Eren, Cansu; Karamzadeh, Saeid; Kartal, Mesut; Istanbul Technical University; Bahcesehir University; Istanbul Technical University
    In this study, we aim to analyze effects of physical motions of human body such as hand movements and speaking during contactless vital signs monitoring. Human respiratory rate (RR) has periodic in nature and its frequency varies between 0.2-0.5Hz for each human. Considering weakness of human vital signs, the analysis of other physical movements of human body on vital signs monitoring should well analyzed to obtain accurate RR results. This situation carries great significance in health-care units which purpose the non-contact and non-invasive monitoring of patients in near future. In order to achieve our goal, an UWB radar system has been used to detect respiratory rate of human body. Mathematical model of human breath signal and theoretical analysis of RR detection using UWB radar has been explained. The spectral estimation of RR has been performed by Fast Fourier Transform (FFT) due to its rapid response and simplicity. The strong noise effects of such physical movements of human body during RR monitoring have been observed and results are presented.