Instantaneous Ego-Motion Estimation Using a Coherent Radar Network
Hoffmann M, Krabbe L, Schüßler C, Gulden P, Vossiek M (2022)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2022
Publisher: IEEE
Event location: Milan, Italy
ISBN: 978-2-8748-7071-2
DOI: 10.23919/EuRAD54643.2022.9924633
Abstract
This paper presents an approach to estimate the ego-motion of a vehicle equipped with a network of two or more coherently working bistatic or multistatic MIMO radars. The multi-perspective view of this setup allows for an immediate determination of the radar targets' relative velocity vector. The ego-motion is then derived from the inverted vectorial velocity of all static targets that can be obtained by clustering the velocity vectors. For this, it can be assumed that the majority of the detected targets are static, thus generating the largest cluster. The novel approach was tested with a setup consisting of two 77 GHz front-looking, long-range radars that only exhibit a narrow field of view with a small azimuth variation. The functionality of the proposed algorithm was evaluated and confirmed in a highway test drive.
Authors with CRIS profile
Marcel Hoffmann
Lehrstuhl für Hochfrequenztechnik
Lena Krabbe
Lehrstuhl für Hochfrequenztechnik
Christian Schüßler
Lehrstuhl für Hochfrequenztechnik
Martin Vossiek
Lehrstuhl für Hochfrequenztechnik
Involved external institutions
United States (USA) (US)How to cite
APA:
Hoffmann, M., Krabbe, L., Schüßler, C., Gulden, P., & Vossiek, M. (2022). Instantaneous Ego-Motion Estimation Using a Coherent Radar Network. In Proceedings of the 2022 19th European Radar Conference (EuRAD). Milan, Italy, IT: IEEE.
MLA:
Hoffmann, Marcel, et al. "Instantaneous Ego-Motion Estimation Using a Coherent Radar Network." Proceedings of the 2022 19th European Radar Conference (EuRAD), Milan, Italy IEEE, 2022.
BibTeX: Download