Robust real-time obstacle detection and tracking is an active challenge in the automotive industry. While, for years, this space was dominated by sensors like LiDAR and cameras, recent technological advancements have allowed an old technology to make a comeback, the radar. This work describes an algorithm capable of performing obstacle detection and tracking using solely Millimeter-Wave radar sensors as an input. This algorithm can be used as a way to evaluate capabilities of mmWave radar systems without resorting to Neural Networks, which require large amounts of data for training.
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Carvalho et al. (2024) studied this question.
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