{"url":"/dataset/simulated-micro-doppler-signatures","name":"Simulated micro-Doppler Signatures","full_name":null,"description_markdown":"Simulated pulse Doppler radar signatures for four classes of helicopter-like targets. The classes differ in the number of rotating blades each kind of target carries, thus each class translates into a specific modulation pattern on the Doppler signature. Doppler signatures are a typical feature used to achieve radar targets discrimination. This dataset was generated using a simple open-source MATLAB [simulation code](https://github.com/Blupblupblup/Doppler-Signatures-Generation), which can be easily modified to generate custom datasets with more classes and increased intra-class diversity. \r\n\r\nDataset can be easily used for supervised classification, out-of-distribution detection (near and far), unsupervised learning and modulation pattern segmentation. The code includes the generation of an SPD representation for each signature, thanks to the computation of a covariance matrix, thus allowing for second-order specific data processing (e.g. Riemannian neural network or tangent PCA).\r\n\r\n[Dataset used in the paper](https://cloud.mbauw.eu/s/BPtk5HYkyBWAGLo)\r\n\r\n[Dataset generation code](https://github.com/Blupblupblup/Doppler-Signatures-Generation)","description_withheld":null,"homepage":"https://cloud.mbauw.eu/s/BPtk5HYkyBWAGLo","introduced_date":"2022-05-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/near-out-of-distribution-detection-for-low","title":"Near out-of-distribution detection for low-resolution radar micro-Doppler signatures","first_author":"Martin Bauw","url":null},"license":{"name":"MIT","url":"https://github.com/Blupblupblup/Doppler-Signatures-Generation"},"modalities":[],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"},{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"},{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Out-of-Distribution Detection","url":"/task/out-of-distribution-detection","datasets_with_task":"/datasets/task/out-of-distribution-detection"},{"name":"One-class classifier","url":"/task/one-class-classifier","datasets_with_task":"/datasets/task/one-class-classifier"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Simulated micro-Doppler Signatures"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}