2026-10-08T18:30:19Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33977674 2026-10-05T07:07:48Z category_26503 category_26524 portal_549 item_type_3 month_year_10_2026

Radar ML - Lite Matt Ritchie (6781985) Ryan White (17035119) Adam Hosford (22753758) Electronic sensors Radio frequency engineering Radar -- Military applications Waveform characteristic Radar and communication system ES <p dir="ltr">This is the "<b>RadarML Lite</b>". It is a sub-set of the complete "<b>RadarML</b>" dataset that has already been released.</p><p dir="ltr">The original <b>RadarML</b> dataset has <b>3 receiver channels: ADC0, ADC2 and ADC4</b>.</p><ul><li><b>648 configurations:</b> 1,000 pulses per channel.</li><li><b>12 configurations:</b> 8,000 pulses per channel.</li></ul><p dir="ltr">Which totals <b>744,000 pulse captures per channel</b>, or <b>2,232,000 channel-specific recordings</b> across all three channels, before SNR augmentation.</p><p dir="ltr">The compact "<b>RadarML Lite" </b>version retains <b>100 pulses per configuration from ADC0 only, </b>which totals <b>66,000 pulses</b>.</p><p dir="ltr">Here is a link to the projects GIT page:</p><p dir="ltr"><b>https://github.com/UCLRadarGroup/Radar_ML/tree/radar-ml-lite</b></p><p dir="ltr">See a further description of the full RadarML dataset below:</p><p dir="ltr">RadarML is a publicly available dataset of experimentally captured modulated radar pulses recorded over-the-air across multiple independent receive channels.</p><p dir="ltr">The dataset was captured on the UCL ARESTOR platform which is a Radio-Frequency-System-on-a-chip (RFSoC). Each waveform was designed based on its central frequency, bandwidth, duration and modulation type. The overall dataset contains over 2 million waveforms across 7 different modulation types. The goal of this dataset is to enable comparative analysis of Radar Modulation Classification techniques on real data and stimulate research into multi-channel signal detection methods.</p><p dir="ltr">Baseline detection and classification results are presented in the linked publication, showing how the performance varies as a function of Signal to Noise ratio.</p> 2026-10-05T07:07:48Z Dataset Dataset 10.5522/04/33977674.v2 https://figshare.com/articles/dataset/Radar_ML_-_Lite/33977674 CC BY-NC-ND 4.0