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Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving

Holder, Martin Friedrich and Rosenberger, Philipp and Winner, Hermann and Dhondt, Thomas and Makkapati, Vamsi Prakash and Maier, Michael and Schreiber, Helmut and Magosi, Zoltan and Slavik, Zora and Bringmann, Oliver and Rosenstiel, Wolfgang (2018):
Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving.
In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, 4-7 Nov. 2018, pp. 2616-2622, DOI: 10.1109/ITSC.2018.8569423,
[Online-Edition: https://doi.org/10.1109/ITSC.2018.8569423],
[Conference or Workshop Item]

Abstract

The virtual validation of automated driving functions requires meaningful simulation models of environment perception sensors such as radar, lidar, and cameras. There does not yet exist an unrivaled standard for perception sensor models, and radar especially lacks modeling approaches that consistently produce realistic results. In this paper, we present measurements that exemplify challenges in the development of meaningful radar sensor models. We highlight three major challenges: multi-path propagation, separability, and sensitivity of radar cross section to the aspect angle. We also review previous work addressing these challenges and suggest further research directions towards meaningful automotive radar simulation models.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Holder, Martin Friedrich and Rosenberger, Philipp and Winner, Hermann and Dhondt, Thomas and Makkapati, Vamsi Prakash and Maier, Michael and Schreiber, Helmut and Magosi, Zoltan and Slavik, Zora and Bringmann, Oliver and Rosenstiel, Wolfgang
Title: Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving
Language: English
Abstract:

The virtual validation of automated driving functions requires meaningful simulation models of environment perception sensors such as radar, lidar, and cameras. There does not yet exist an unrivaled standard for perception sensor models, and radar especially lacks modeling approaches that consistently produce realistic results. In this paper, we present measurements that exemplify challenges in the development of meaningful radar sensor models. We highlight three major challenges: multi-path propagation, separability, and sensitivity of radar cross section to the aspect angle. We also review previous work addressing these challenges and suggest further research directions towards meaningful automotive radar simulation models.

Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD)
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Driver Assistance
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Safety
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Test Methods
Event Title: 2018 21st International Conference on Intelligent Transportation Systems (ITSC)
Event Location: Maui, HI, USA
Event Dates: 4-7 Nov. 2018
Date Deposited: 24 Nov 2019 20:55
DOI: 10.1109/ITSC.2018.8569423
Official URL: https://doi.org/10.1109/ITSC.2018.8569423
URN: urn:nbn:de:tuda-tuprints-92779
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