Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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  • Article
    Citation - WoS: 1
    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
    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.