To gain access to the dataset, please contact Felix Rutz (felix.rutz@tum.de).
The dataset contains raw radar data from a 77 GHz FMCW-Radar. The data was gathered driving in the surrounding area of the TUM. Object lists (pedestrians, cyclists and cars) were created with the help of reference sensors. The objects are saved as slices, also called regions of interest (ROI), of the radar range-Doppler-angle spectrum.
This dataset is meant for reproducing the results presented in the publication: Pérez, R., Schubert, F., Rasshofer, R., and Biebl, E.: A machine learning joint lidar and radar classification system in urban automotive scenarios, Adv. Radio Sci., 17, 129–136, doi:10.5194/ars-17-129-2019, 2019
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To gain access to the dataset, please contact Felix Rutz (felix.rutz@tum.de).
The dataset contains raw radar data from a 77 GHz FMCW-Radar. The data was gathered driving in the surrounding area of the TUM. Object lists (pedestrians, cyclists and cars) were created with the help of reference sensors. The objects are saved as slices, also called regions of interest (ROI), of the radar range-Doppler-angle spectrum.
This dataset is meant for reproducing the results presented in the publication: Pére...
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