Analysis of Automotive Radar Interference Mitigation for Real-World Environments

M. Toth; J. Rock; P. Meissner; A. Melzer; K. Witrisal

doi:10.1109/EuRAD48048.2021.00054

Analysis of Automotive Radar Interference Mitigation for Real-World Environments

M. Toth, J. Rock, P. Meissner, A. Melzer, K. Witrisal

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

Abstract

The critical issue of mutual interference in automotive radar leads to a growing number of processing algorithms for mitigation. Analyses of their performance have been mostly based on either simulations or on a small number of exemplary measurements. In this contribution, a corpus of real-world radar measurements is used, to which strongly varying simulated interferences are added. A statistical analysis framework is then applied to a set of state-of-the-art mitigation algorithms, studying the impact of highly complex object environments on their performance.

Original language	English
Title of host publication	EuRAD 2020 - 2020 17th European Radar Conference
Pages	176-179
Number of pages	4
ISBN (Electronic)	9782874870613
DOIs	https://doi.org/10.1109/EuRAD48048.2021.00054
Publication status	Published - 2021
Event	17th European Radar Conference: EuRAD 2020 - Virtuell, Utrecht, Netherlands Duration: 13 Jan 2021 → 15 Jan 2021

Conference

Conference	17th European Radar Conference
Abbreviated title	EuRAD 2020
Country/Territory	Netherlands
City	Virtuell, Utrecht
Period	13/01/21 → 15/01/21

Keywords

automotive components
millimeter wave radar
radar signal processing
radiofrequency interference
sensor systems

ASJC Scopus subject areas

Signal Processing
Instrumentation
Computer Networks and Communications

Access to Document

10.1109/EuRAD48048.2021.00054

Cite this

@inproceedings{274196dde6ce4e70a9dfea051b265077,

title = "Analysis of Automotive Radar Interference Mitigation for Real-World Environments",

abstract = "The critical issue of mutual interference in automotive radar leads to a growing number of processing algorithms for mitigation. Analyses of their performance have been mostly based on either simulations or on a small number of exemplary measurements. In this contribution, a corpus of real-world radar measurements is used, to which strongly varying simulated interferences are added. A statistical analysis framework is then applied to a set of state-of-the-art mitigation algorithms, studying the impact of highly complex object environments on their performance.",

keywords = "automotive components, millimeter wave radar, radar signal processing, radiofrequency interference, sensor systems",

author = "M. Toth and J. Rock and P. Meissner and A. Melzer and K. Witrisal",

year = "2021",

doi = "10.1109/EuRAD48048.2021.00054",

language = "English",

pages = "176--179",

booktitle = "EuRAD 2020 - 2020 17th European Radar Conference",

note = "17th European Radar Conference : EuRAD 2020, EuRAD 2020 ; Conference date: 13-01-2021 Through 15-01-2021",

}

TY - GEN

T1 - Analysis of Automotive Radar Interference Mitigation for Real-World Environments

AU - Toth, M.

AU - Rock, J.

AU - Meissner, P.

AU - Melzer, A.

AU - Witrisal, K.

PY - 2021

Y1 - 2021

N2 - The critical issue of mutual interference in automotive radar leads to a growing number of processing algorithms for mitigation. Analyses of their performance have been mostly based on either simulations or on a small number of exemplary measurements. In this contribution, a corpus of real-world radar measurements is used, to which strongly varying simulated interferences are added. A statistical analysis framework is then applied to a set of state-of-the-art mitigation algorithms, studying the impact of highly complex object environments on their performance.

AB - The critical issue of mutual interference in automotive radar leads to a growing number of processing algorithms for mitigation. Analyses of their performance have been mostly based on either simulations or on a small number of exemplary measurements. In this contribution, a corpus of real-world radar measurements is used, to which strongly varying simulated interferences are added. A statistical analysis framework is then applied to a set of state-of-the-art mitigation algorithms, studying the impact of highly complex object environments on their performance.

KW - automotive components

KW - millimeter wave radar

KW - radar signal processing

KW - radiofrequency interference

KW - sensor systems

UR - http://www.scopus.com/inward/record.url?scp=85100904582&partnerID=8YFLogxK

U2 - 10.1109/EuRAD48048.2021.00054

DO - 10.1109/EuRAD48048.2021.00054

M3 - Conference paper

SP - 176

EP - 179

BT - EuRAD 2020 - 2020 17th European Radar Conference

T2 - 17th European Radar Conference

Y2 - 13 January 2021 through 15 January 2021

ER -

Analysis of Automotive Radar Interference Mitigation for Real-World Environments

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

InterCEPT - Interference Mitigation Concepts and Efficient Processing

Cite this

Analysis of Automotive Radar Interference Mitigation for Real-World Environments

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

InterCEPT - Interference Mitigation Concepts and Efficient Processing

Cite this