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

Martin Holder; Philpp Rosenberger; Hermann Winner; Thomas  D'hondt; Vamsi Prakash Makkapati; Franz Michael Maier; Helmut Schreiber; Zoltan Ferenc Magosi; Zora Slavik; Oliver Bringmann; Wolfgang Rosenstiel

doi:10.1109/ITSC.2018.8569423

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

Martin Holder, Philpp Rosenberger, Hermann Winner, Thomas D'hondt, Vamsi Prakash Makkapati, Franz Michael Maier, Helmut Schreiber, Zoltan Ferenc Magosi, Zora Slavik, Oliver Bringmann, Wolfgang Rosenstiel

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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.

Original language	English
Title of host publication	2018 21st International Conference on Intelligent Transportation Systems (ITSC)
Pages	2616 - 2622
Number of pages	6
DOIs	https://doi.org/10.1109/ITSC.2018.8569423
Publication status	Published - 4 Nov 2018
Event	21st IEEE International Conference on Intelligent Transportation Systems: ITSC 2018 - Maui, United States Duration: 4 Nov 2018 → 7 Nov 2018 https://www.ieee-itsc2018.org/

Conference

Conference	21st IEEE International Conference on Intelligent Transportation Systems
Abbreviated title	ITSC 2018
Country/Territory	United States
City	Maui
Period	4/11/18 → 7/11/18
Internet address	https://www.ieee-itsc2018.org/

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10.1109/ITSC.2018.8569423

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Holder, M., Rosenberger, P., Winner, H., D'hondt, T., Makkapati, V. P., Maier, F. M., Schreiber, H., Magosi, Z. F., Slavik, Z., Bringmann, O., & Rosenstiel, W. (2018). Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC) (pp. 2616 - 2622) https://doi.org/10.1109/ITSC.2018.8569423

Holder, M, Rosenberger, P, Winner, H, D'hondt, T, Makkapati, VP, Maier, FM, Schreiber, H , Magosi, ZF, Slavik, Z, Bringmann, O & Rosenstiel, W 2018, Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving. in 2018 21st International Conference on Intelligent Transportation Systems (ITSC). pp. 2616 - 2622, 21st IEEE International Conference on Intelligent Transportation Systems, Maui, Hawaii, United States, 4/11/18. https://doi.org/10.1109/ITSC.2018.8569423

@inproceedings{b5f42c001a5a4a7e8c2fafe0fd9c51f8,

title = "Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving",

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.",

author = "Martin Holder and Philpp Rosenberger and Hermann Winner and Thomas D'hondt and Makkapati, {Vamsi Prakash} and Maier, {Franz Michael} and Helmut Schreiber and Magosi, {Zoltan Ferenc} and Zora Slavik and Oliver Bringmann and Wolfgang Rosenstiel",

year = "2018",

month = nov,

day = "4",

doi = "10.1109/ITSC.2018.8569423",

language = "English",

isbn = "978-1-7281-0321-1 ",

pages = "2616 -- 2622",

booktitle = "2018 21st International Conference on Intelligent Transportation Systems (ITSC)",

note = "21st IEEE International Conference on Intelligent Transportation Systems : ITSC 2018, ITSC 2018 ; Conference date: 04-11-2018 Through 07-11-2018",

url = "https://www.ieee-itsc2018.org/",

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AU - Holder, Martin

AU - Rosenberger, Philpp

AU - Winner, Hermann

AU - D'hondt, Thomas

AU - Makkapati, Vamsi Prakash

AU - Maier, Franz Michael

AU - Schreiber, Helmut

AU - Magosi, Zoltan Ferenc

AU - Slavik, Zora

AU - Bringmann, Oliver

AU - Rosenstiel, Wolfgang

PY - 2018/11/4

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N2 - 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.

AB - 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.

U2 - 10.1109/ITSC.2018.8569423

DO - 10.1109/ITSC.2018.8569423

M3 - Conference paper

SN - 978-1-7281-0321-1

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EP - 2622

BT - 2018 21st International Conference on Intelligent Transportation Systems (ITSC)

T2 - 21st IEEE International Conference on Intelligent Transportation Systems

Y2 - 4 November 2018 through 7 November 2018

ER -

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

Abstract

Conference

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