Randolf Ebelt

Randolf Ebelt serves as Professor and Chair of High Frequency Engineering within the Department of Electrical Engineering, Electronics and Information Technology (EEI) at FAU's Faculty of Engineering. His research focuses on radar systems and wireless localization technologies with applications in automotive and indoor environments.

His primary research interests include automotive radar signal processing, deep learning applications for radar enhancement, and wireless sensor networks for precise localization. He has pioneered work in ghost detection identification, MIMO radar arrays, and 24 GHz transceiver design for real-time 3D positioning systems.

Analysis of his publication trends shows increasing integration of artificial intelligence with traditional radar engineering since 2019, particularly using deep learning for automotive radar enhancement and ghost detection. His work consistently addresses practical implementation challenges including phase noise effects, antenna array optimization, and multipath mitigation in complex environments.

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Professor Ebelt leads the Chair of High Frequency Engineering (LHFT) research group at FAU, which maintains active collaborations with industry partners on radar technology development and participates in international research initiatives focused on automotive and wireless positioning systems.