Effects of Dust and Moisture Surface Contaminants on Automotive Radar Sensor Frequencies

Perception and sensing of the surrounding environment are crucial for ensuring the safety of autonomous driving systems. A key issue is securing sensor reliability from sensors mounted on the vehicle and obtaining accurate raw data. Surface contamination in front of a sensor typically occurs due to adverse weather conditions or particulate matter on the road, which can degrade system reliability depending on sensor placement and surrounding bodywork geometry. Moreover, the moisture content of dust contaminants can cause surface adherence, making it more likely to persist on a vertical sensor surface compared to moisture only. In this work, a 76-81 GHz radar sensor, a 72-82 GHz automotive radome tester, a 60-90 GHz vector network analyzer system, and a 76-81 GHz radar target simulator setup were used in combination with a representative polypropylene plate that was purposefully contaminated with a varying range of water and ISO standard dust combinations; this was used to determine any signal attenuation and subsequent impact on target detection. The results show that the water content in dust contaminants significantly affects radar signal transmission and object detection performance, with higher water content levels causing increased signal attenuation, impacting detection capability across all tested scenarios.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-03-30
DOI
https://doi.org/10.3390/s25072192
Citations
4
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
3.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of Dust and Moisture Surface Contaminants on Automotive Radar Sensor Frequencies

Tobias Eidevåg, Ross J. Friel, Vanäs Karl, Emil Nilsson et al.
4 citations
Sensors
Engineering Applied Research
3.81
article

Effects of Dust and Moisture Surface Contaminants on Automotive Radar Sensor Frequencies

Tobias Eidevåg, Ross J. Friel, Vanäs Karl, Emil Nilsson, J. H. Kang, Hamidi Oskar
article en
4 citations

Abstract

Perception and sensing of the surrounding environment are crucial for ensuring the safety of autonomous driving systems. A key issue is securing sensor reliability from sensors mounted on the vehicle and obtaining accurate raw data. Surface contamination in front of a sensor typically occurs due to adverse weather conditions or particulate matter on the road, which can degrade system reliability depending on sensor placement and surrounding bodywork geometry. Moreover, the moisture content of dust contaminants can cause surface adherence, making it more likely to persist on a vertical sensor surface compared to moisture only. In this work, a 76-81 GHz radar sensor, a 72-82 GHz automotive radome tester, a 60-90 GHz vector network analyzer system, and a 76-81 GHz radar target simulator setup were used in combination with a representative polypropylene plate that was purposefully contaminated with a varying range of water and ISO standard dust combinations; this was used to determine any signal attenuation and subsequent impact on target detection. The results show that the water content in dust contaminants significantly affects radar signal transmission and object detection performance, with higher water content levels causing increased signal attenuation, impacting detection capability across all tested scenarios.

SensorsVol. 25(7)
Volvo (Sweden) (SE), Volvo Cars (Sweden), Halmstad University (SE)
Openalex Percentile: Top 8%
Engineering Applied Research
3.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Effects of Dust and Moisture Surface Contaminants on Automotive Radar Sensor Frequencies — Tobias Eidevåg, Ross J. Friel, et al. · Sensors (2025) | TGRS Research Map | TGRS