Influence of Real-World Appearance Variations on the Radar Signature of a Pedestrian Soft Target

Validation of Advanced Driver Assistance Systems (ADAS) relies on standardized pedestrian soft targets to ensure comparable safety assessment. However, real-world pedestrians differ from standardized targets in clothing and carried objects, potentially altering radar-based sensing. This exploratory study investigates how such variations affect the sensor-reported apparent radar cross section (RCS) of a pedestrian soft target. Eight configurations were evaluated on a closed proving ground. For each configuration, one 30 s stationary measurement at approximately 5 m and three vehicle-approach runs ranging from 30 to 5 m were performed using a vehicle-mounted automotive radar. Dynamic runs were evaluated in three distance bands using run-level median apparent RCS values, differences from the reference, and run-to-run standard deviation. The backpack and notebook bag produced the largest observed positive deviations, reaching +9.17 and +7.25 dB at 20–30 m. The visibility vest showed a moderate, consistent positive shift, whereas the winter coat and jacket remained closer to the reference in most bands. The umbrella configuration exhibited the greatest run-to-run variability. Among the investigated configurations, the largest observed differences were associated with the backpack and notebook bag, both of which substantially altered the external shape of the pedestrian surrogate. Because only three dynamic repetitions, one radar sensor, one pedestrian surrogate, and one side-profile orientation were investigated, the findings should be interpreted as an exploratory, sensor-specific sensitivity analysis rather than as a definitive characterization of pedestrian RCS or ADAS performance.

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Publication Details

Journal
Future Transportation
Published
2026-10-15
DOI
https://doi.org/10.3390/futuretransp6050231
Primary Topic
Radar Systems and Signal Processing
Type
article
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article

Influence of Real-World Appearance Variations on the Radar Signature of a Pedestrian Soft Target

Gábor László Tóth, Norbert Simon
Future Transportation
Radar Systems and Signal Processing
article

Influence of Real-World Appearance Variations on the Radar Signature of a Pedestrian Soft Target

Gábor László Tóth, Norbert Simon
article en

Abstract

Validation of Advanced Driver Assistance Systems (ADAS) relies on standardized pedestrian soft targets to ensure comparable safety assessment. However, real-world pedestrians differ from standardized targets in clothing and carried objects, potentially altering radar-based sensing. This exploratory study investigates how such variations affect the sensor-reported apparent radar cross section (RCS) of a pedestrian soft target. Eight configurations were evaluated on a closed proving ground. For each configuration, one 30 s stationary measurement at approximately 5 m and three vehicle-approach runs ranging from 30 to 5 m were performed using a vehicle-mounted automotive radar. Dynamic runs were evaluated in three distance bands using run-level median apparent RCS values, differences from the reference, and run-to-run standard deviation. The backpack and notebook bag produced the largest observed positive deviations, reaching +9.17 and +7.25 dB at 20–30 m. The visibility vest showed a moderate, consistent positive shift, whereas the winter coat and jacket remained closer to the reference in most bands. The umbrella configuration exhibited the greatest run-to-run variability. Among the investigated configurations, the largest observed differences were associated with the backpack and notebook bag, both of which substantially altered the external shape of the pedestrian surrogate. Because only three dynamic repetitions, one radar sensor, one pedestrian surrogate, and one side-profile orientation were investigated, the findings should be interpreted as an exploratory, sensor-specific sensitivity analysis rather than as a definitive characterization of pedestrian RCS or ADAS performance.

Future TransportationVol. 6(5)
Sustainable cities and communities
Openalex Percentile: Top 18%
Radar Systems and Signal Processing
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