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 IT

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 (LHFT) Lena Krabbe Lehrstuhl für Hochfrequenztechnik (LHFT) Christian Schüßler Lehrstuhl für Hochfrequenztechnik (LHFT) Martin Vossiek Lehrstuhl für Hochfrequenztechnik (LHFT)

Involved external institutions

Indie Semiconductor US 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.

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