Sven Hinderer

M.Sc.

Research Assistant
Institute of Signal Processing and System Theory

Contact

+49 711 685 67359
+49 711 685 67311

Pfaffenwaldring 47
70569 Stuttgart
Germany
Room: 2.275

Office Hours

Nach Vereinbarung.

Subject

Single-channel radar-based indoor localization with passive reflectors.

Indoor localization has seen an emerging interest over the last years. As Global Navigation Satellite System (GNSS) signals cannot be used indoors, dedicated systems have to be deployed for indoor localization. 
Indoor positioning systems (IPS) based on millimeter (mm) waves offer high accuracy by using the ultra-wideband (UWB) approach, i.e. waveforms with large bandwidth. However, current UWB systems suffer from high system complexity and cost. We propose a millimeter wave indoor localization system based on active radar sensing of local passive reference points (LRPs) that promises highly accurate and reliable indoor localization at low system cost. This system shall be used to navigate autonomous mobile robots (AMRs) in indoor environments.

Sven Hinderer, Pascal Schlachter, Zhibin Yu, Xiaofeng Wu, Bin Yang, "Indoor Positioning based on Active Radar Sensing and Passive Reflectors: Reflector Placement Optimization", 2023 International Conference on
Indoor Positioning and Indoor Navigation, Nürnberg, Germany, 2023

Pascal Schlachter, Zhibin Yu, Naveed Iqbal, Xiaofeng Wu, Sven Hinderer, Bin Yang, "Indoor Positioning based on Active Radar Sensing and Passive Reflectors: Concepts & Initial Results", 2023 International Conference on Indoor Positioning and Indoor Navigation, Nürnberg, Germany, 2023

S. Hinderer, "Blind Source Separation of Radar Signals in Time Domain Using Deep Learning", 2022 International Radar Symposium, Gdańsk, Poland, 2022

Organization & Tensorflow Introduction for "Deep Learning" course

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