On the Advantages of Coherent Automotive Radar Networks for Occupancy Gridmapping

Sura O, Euler M, Heidbrink M, Hoffmann M, Gulden P, Vossiek M (2024)

Publication Type: Conference contribution

Publication year: 2024

Publisher: IEEE

City/Town: New York City

Pages Range: 348-351

Conference Proceedings Title: 2024 21st European Radar Conference (EuRAD)

Event location: Paris

DOI: 10.23919/EuRAD61604.2024.10734872

Abstract

Autonomous driving requires a robust and detailed perception of the environment even under harsh environmental conditions. Radar sensors can play an integral part in reaching this goal. However, compared to lidar, radar data suffer from lower angular resolution and sparser and noisier point clouds. While occupancy gridmapping has proven to be a valuable mapping tool for clutter-prone point clouds, coherent radar networks provide a promising solution for high-resolution radar imaging. Consequently, this paper evaluates the use of a coherent radar network in combination with occupancy gridmapping to demonstrate the benefit of a coherent bistatic radar network consisting of two stations compared to incoherently operating radar systems. It is demonstrated that the occupancy gridmaps obtained with the coherent network are superior to the standard incoherent system in terms of resolution, number of detected targets, and vectorial velocity estimation.

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Additional Organisation(s)

Involved external institutions

Indie Semiconductor United States (USA) (US)

How to cite

APA:

Sura, O., Euler, M., Heidbrink, M., Hoffmann, M., Gulden, P., & Vossiek, M. (2024). On the Advantages of Coherent Automotive Radar Networks for Occupancy Gridmapping. In 2024 21st European Radar Conference (EuRAD) (pp. 348-351). Paris, FR: New York City: IEEE.

MLA:

Sura, Oliver, et al. "On the Advantages of Coherent Automotive Radar Networks for Occupancy Gridmapping." Proceedings of the 2024 21st European Radar Conference (EuRAD), Paris New York City: IEEE, 2024. 348-351.

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