@inproceedings{52c556b94e1046a2bd30c2de197797f3,
title = "AUTOMATED LABELING OF AUTOMOTIVE RADAR AZIMUTH MULTIPATH",
abstract = "Automotive radars are the key component in the autonomous vehicle's sensing suite. Their role is particularly crucial in dense urban environments characterized by multipath propagation conditions induced by reflections from flat surfaces. Multipath propagation phenomena may generate'ghost' targets that can degrade radar performance. Deep neural network (DNN) based radar signal processing can address the multipath-induce phenomena. However, it requires the availability of extensive and annotated databases. Publically available automotive radar datasets lack accurately labeled multipath-induced {"}ghost{"} targets. Therefore, they are inappropriate for DNN-based radar processing. This work introduces an automated multipath annotation approach to transform conventional datasets into multipath-labeled ones. The derived approach provides detailed {"}ghost{"} targets and reflector labels, distinguishing actual targets from reflectors, identifying reflector types, and estimating multipath reflection order. The performance of the proposed labeling approach is evaluated using a manually labeled real-world multipath dataset, demonstrating its effectiveness in annotating multipath radar detections and facilitating DNN-based automotive radar processing in multipath-dominated urban environments.",
keywords = "Automatic Annotation, Automotive Radar, Dataset, Labeling, LiDAR, Multipath",
author = "Stav Danino and Igal Bilik",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 ; Conference date: 14-04-2024 Through 19-04-2024",
year = "2024",
month = jan,
day = "1",
doi = "10.1109/ICASSP48485.2024.10446232",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "7630--7634",
booktitle = "2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings",
address = "United States",
}