Achieving Efficient and Realistic Full-Radar Simulations and Automatic Data Annotation by Exploiting Ray Meta Data from a Radar Ray Tracing Simulator
Schüßler C, Hoffmann M, Wirth V, Eskofier B, Weyrich T, Stamminger M, Vossiek M (2023)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2023
Publisher: IEEE Xplore
Conference Proceedings Title: IEEE Xplore
Event location: 2023 IEEE Radar Conference (RadarConf23). San Antonio, TX, US
ISBN: 978-1-6654-3669-4
DOI: 10.1109/RadarConf2351548.2023.10149641
Abstract
In this work, a novel radar simulation concept for efficiently simulating realistic radar data for range, Doppler, and arbitrary antenna positions is introduced. With the concept, the simulated radar signal can also be automatically annotated by splitting it into multiple parts. Annotations that are almost perfect - including the annotation of exotic effects, such as multi-path - can be produced with this approach. Signal parts originating from different parts of an object can be labelled with it as well. To this end, the computation process used in a Monte Carlo shooting and bouncing rays (SBR) simulator is adapted. By considering the hits of each simulated ray, various meta data can be stored, such as hit position, mesh pointer, object IDs, and many more. This collected meta data can then be utilized to predict path-length changes caused by object motion to obtain Doppler information or to apply specific ray filter rules to obtain radar signals that only fulfil specific conditions, such as multiple bounces, or signals that contain specific object IDs. Using this approach, perfect, and otherwise almost impossible, annotation schemes can be realized.
Authors with CRIS profile
Christian Schüßler
Lehrstuhl für Hochfrequenztechnik (LHFT)
Marcel Hoffmann
Lehrstuhl für Hochfrequenztechnik (LHFT)
Vanessa Wirth
Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung (EmpkinS)
Björn Eskofier
Machine Learning and Data Analytics Lab
Tim Weyrich
Lehrstuhl für Informatik 15 (Digital Reality)
Marc Stamminger
Chair of Visual Computing (LGDV)
Martin Vossiek
Lehrstuhl für Hochfrequenztechnik (LHFT)
Additional Organisation(s)
How to cite
APA:
Schüßler, C., Hoffmann, M., Wirth, V., Eskofier, B., Weyrich, T., Stamminger, M., & Vossiek, M. (2023). Achieving Efficient and Realistic Full-Radar Simulations and Automatic Data Annotation by Exploiting Ray Meta Data from a Radar Ray Tracing Simulator. In Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (Grant Number: 44241933) (Eds.), IEEE Xplore. 2023 IEEE Radar Conference (RadarConf23). San Antonio, TX, US, US: IEEE Xplore.
MLA:
Schüßler, Christian, et al. "Achieving Efficient and Realistic Full-Radar Simulations and Automatic Data Annotation by Exploiting Ray Meta Data from a Radar Ray Tracing Simulator." Proceedings of the 2023 IEEE Radar Conference (RadarConf23), 2023 IEEE Radar Conference (RadarConf23). San Antonio, TX, US Ed. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (Grant Number: 44241933), IEEE Xplore, 2023.
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