"Raw mmWave Radar Dataset of Pollinating Insects for Micro-Doppler-Based Classification and Learning"

"This dataset contains raw continuous-wave (CW) millimeter-wave (mmWave) radar signals collected for the analysis and classification of flying pollinators based on their micro-Doppler signatures. The data was acquired using a 30 GHz CW radar system, capturing backscattered signals from freely flying insects under controlled experimental conditions.The dataset includes measurements from five pollinator species: Apis mellifera, Vespula vulgaris, Bombus terrestris, Bombus lapidarius, and Bombus muscorum. Each recording captures the temporal variations in the reflected signal caused by wingbeat-induced micro-motions, enabling detailed investigation of harmonic structures and species-specific flight characteristics.Each measurement consists of raw radar returns recorded over a duration of 60 seconds, with 60,001 samples per recording. The signals are stored in CSV format, containing two columns representing the amplitude and phase of the received signal. No preprocessing or feature extraction has been applied, allowing researchers to directly explore raw signal processing, micro-Doppler analysis, and machine learning approaches.Ground truth labels are embedded within the file names, encoding species identity, subject instance, and measurement index. "