"Multi-Configuration FMCW Radar Dataset for Hand Gesture Recognition"

"Frequency-modulated continuous wave (FMCW) radar offers a highly robust, privacy-preserving alternative to traditional optical sensors for hand gesture recognition. However, a major bottleneck in deploying radar-based neural networks is their sensitivity to sensor configuration shifts. Models trained on a fixed set of radar parameters frequently suffer from severe performance degradation when real-world application requirements necessitate changes to bandwidth, sampling rate, or chirp timing.To bridge this gap and drive research in configuration-agnostic learning, we introduce a comprehensive, large-scale multi-configuration radar dataset. This benchmark contains 72,000 independent gesture samples, capturing a diverse range of signal distributions. The data was recorded across 24 distinct radar configurations. Furthermore, to ensure hardware diversity and account for slight manufacturing variations, the dataset was collected using three separate physical Infineon XENSIV\u2122 BGT60TR13C 60GHz FMCW radar sensors.We believe this dataset will be an invaluable resource for the machine learning and signal processing communities. By providing explicit, systematic distributional shifts, we hope to accelerate the development of continual learning mechanisms, universal radar foundation models, and adaptive human-computer interaction systems that operate seamlessly regardless of the underlying radar setup. This dataset is a contribution of our paper submitted to the European Radar Conference (EuRAD) at the European Microwave Week 2026. To the best of our knowledge, it represents the largest open-source multi-configuration radar dataset available to date."