Browsing by Author "Gashinova, Marina"

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Burg-Aided 2D MIMO Array Extrapolation for Improved Spatial Resolution
(MDPI, 2025) Bekar, Muge; Bekar, Ali; Pirkani, Anum; Baker, Christopher John; Gashinova, Marina; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
In this paper, the extrapolation of a 2D multiple-input multiple-output (MIMO) array is proposed using the Burg algorithm to achieve higher angular resolution beyond that of the corresponding 2D MIMO virtual array. The main advantage of such an approach is that it allows us to dramatically decrease both the physical size and the number of antenna elements of the MIMO array. The performance and limitations of the Burg algorithm are examined through both simulation and experimentation at 77 GHz. The experimental methodology used to acquire 3D data of range, azimuth and elevation information with the 1D MIMO off-the-shelf radar is described. Using this method, the performance of the proposed array can be tested experimentally, especially at frequencies where it is desired to assess the antenna response prior to fabricating the antenna.
High-Resolution Augmented Multimodal Sensing of Distributed Radar Network
(IEEE-Inst Electrical Electronics Engineers Inc, 2025) Pirkani, Anum; Kumar, Dillon; Hoare, Edward; Bekar, Muge; Reeves, Natalie; Cherniakov, Mikhail; Gashinova, Marina; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
Advancement toward fully autonomous systems requires enhanced sensing and perception, particularly a 360 degrees vision for safe maneuvering. One approach to achieving this is through a distributed network of radar sensors, operating in homogeneous or heterogeneous configurations, strategically positioned to provide increased coverage and visibility in otherwise blind regions. Such a multiperspective sensing network, complemented with multimodal signal processing, can significantly improve the angular resolution of the radar, delivering high-fidelity scene imagery essential for region classification and path planning. This study presents a methodology for multimodal and multiperspective sensing using heterogeneous radar sensors, utilizing Doppler beam sharpening (DBS) within multiple-input-multiple-output (MIMO) radars to enhance the resolution and coverage. Traditional frequency-modulated continuous wave (FMCW)-MIMO radars, currently the most widely used configuration, are prone to Doppler aliasing, limiting the field of view (FoV) in DBS and MIMO-DBS processing. To address this limitation, the effective FoV in multiperspective image is extended to that provided by the radar's physical aperture. The proposed framework is validated using 77-GHz radar chipsets in both automotive and maritime conditions, with sensors mounted in front-looking, corner-looking, and side-looking orientations.
Oscillator Phase Noise Impact on Monostatic/Bistatic Space-Borne Sub-THz ISAR
(IEEE, 2025) Bekari, Ali; Gashinova, Marina; Bekar, Muge; Martorellai, Marco; Antonioni, Michail; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
This study develops an oscillator phase noise model and analyzes its effects on the performance of spaceborne monostatic and bistatic Inverse Synthetic Aperture Radar (B-ISAR) systems operating at the sub-THz band. The B-ISAR study is of current importance as it can provide a basis for distributed space-based ISAR to enable persistent co-operative space domain awareness (Co-SDA).