# Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS

## TL;DR

This paper introduces an automated method for labeling automotive radar data using highly accurate GNSS, significantly reducing manual effort while maintaining labeling accuracy, and providing a reliable ground truth for system validation.

## Contribution

The paper presents a novel automated labeling system utilizing GNSS for automotive radar data, improving efficiency and accuracy over manual annotation methods.

## Key findings

- Automated labeling reduces annotation time significantly.
- The method maintains comparable accuracy to manual labeling.
- System provides reliable ground truth for validation purposes.

## Abstract

Annotating automotive radar data is a difficult task. This article presents an automated way of acquiring data labels which uses a highly accurate and portable global navigation satellite system (GNSS). The proposed system is discussed besides a revision of other label acquisitions techniques and a problem description of manual data annotation. The article concludes with a systematic comparison of conventional hand labeling and automatic data acquisition. The results show clear advantages of the proposed method without a relevant loss in labeling accuracy. Minor changes can be observed in the measured radar data, but the so introduced bias of the GNSS reference is clearly outweighed by the indisputable time savings. Beside data annotation, the proposed system can also provide a ground truth for validating object tracking or other automated driving system applications.