MSc R Guendel

PhD student
Microwave Sensing, Signals and Systems (MS3), Department of Microelectronics

Expertise: Monitoring of continuous human activities in range and time beyond micro-Doppler by using RF-sensing technology.

Biography

Ronny Gündel received his Diploma-Engineering (FH) (Dipl.-Ing. (FH)) degree at the University of Applied Sciences in Zwickau in January 2017. During his studies, he was employed for 2.5 years as a student researcher at the Fraunhofer Institute for Machine Tools and Forming Technology in Chemnitz (IWU). For the last quarter of employment, the Fraunhofer institute operated as the practical partner for the diploma-thesis. The thesis for a reliable image transmission for a multi-camera-system was selected as an outstanding thesis from the University. In 2017/18 he joined Villanova University (USA) as a Fulbright scholar for a graduate program in Electrical Engineering. Over summer 2018, he worked on wireless communications for vehicular connectivity as a visitor at the Vodafone Char Dresden under Prof. Gerhard Fettweis. In 2018/2019, the Center for Advanced Communications of Villanova University offered him a research assistantship under the guidance of Dr. Moeness G. Amin, working on radar classification of consecutive and contiguous human motions with an industry partner in Philadelphia. Besides the industrial work, he graduated with a Master of Science degree in Signal Processing and Communications in 2019. Ronny Gündel joined TU Delft in January 2020, in the MS3 (Microwave Sensing Signals & Systems) section led by Prof. Alexander Yarovoy within the Department of Microelectronics. Currently, he is working on monitoring of continuous human activities in range and time beyond micro-Doppler by using RF-sensing technology.

Publications

  1. Radar classifications of consecutive and contiguous human gross-motor activities
    Moeness G. Amin; Ronny G. Guendel;
    IET Radar, Sonar Navigation,
    Volume 14, Issue 9, pp. 1417-1429, 09 2020. DOI: 10.1049/iet-rsn.2019.0585

  2. Phase-based Classification for Arm Gesture and Gross-Motor Activities using Histogram of Oriented Gradients
    R. G. Guendel; F. Fioranelli; A. Yarovoy;
    IEEE Sensors Journal,
    pp. 10, 12 2020. DOI: 10.1109/JSEN.2020.3044675

  3. Radar Human Motion Recognition Using Motion States and Two-Way Classifications
    Moeness G. Amin; Ronny G. Guendel;
    In 2020 IEEE International Radar Conference (RADAR),
    pp. 1046-1051, 2020. DOI: 10.1109/RADAR42522.2020.9114613

  4. Derivative Target Line (DTL) for Continuous Human Activity Detection and Recognition
    R. G. Guendel; F. Fioranelli; A. Yarovoy;
    In 2020 IEEE Radar Conference (RadarConf20),
    pp. 1-6, 2020. DOI: 10.1109/RadarConf2043947.2020.9266383

  5. Radar Classification of Contiguous Activities of Daily Living
    Ronny Gerhard Guendel;
    MSc thesis, 2020.

  6. Automatic Arm Motion Recognition Using Radar for Smart Home Technologies
    Moeness G. Amin; Z. Zeng; T. Shan; Ronny G. Guendel;
    In 2019 International Radar Conference (RADAR),
    pp. 1-4, 2019. DOI: 10.1109/RADAR41533.2019.171318

  7. RF sensing for continuous monitoring of human activities for home consumer applications
    Moeness G. Amin; Arun Ravisankar; Ronny G. Guendel;
    In Fauzia Ahmad (Ed.), Big Data: Learning, Analytics, and Applications,
    SPIE, International Society for Optics and Photonics, pp. 33 -- 44, 2019. DOI: 10.1117/12.2519984
    Keywords: ... Radar, indoor monitoring, smart homes, motion classification.

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Last updated: 3 Dec 2020