Data provided by National Institute of Standards and Technology
The RF dataset can be used to develop and test detection algorithms for the 3.5 GHz CBRS or similar bands where the primary users of the band are federal incumbent radar systems. The dataset consists of synthetically generated radar waveforms with added white Gaussian noise. The RF dataset is suitable for development and testing of machine/deep learning detection algorithms. A large number of parameters of the waveforms are randomized across the dataset. Due to its large size, the dataset is divided into groups, and each group consists of multiple files. For more information about the dataset, refer to: R. Caromi, M. Souryal, and T. Hall "RF Dataset of Incumbent Radar Signals in the 3.5 GHz CBRS Band," J Res Natl Inst Stan 124:124038, 2019. available online at: https://doi.org/10.6028/jres.124.038. In addition, the metadata of the dataset is summarized in "Data Dictionary of 3.5 GHz Radar Waveforms" [pdf] accompanying the data. For more information about the motivation behind this RF dataset, refer to: T. Hall, R. Caromi, M. Souryal, and A. Wunderlich, "Reference Datasets for Training and Evaluating RF Signal Detection and Classification Models," in Proc. IEEE GLOBECOM Workshop on Advancements in Spectrum Sharing, Dec. 2019, available online at: https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928336.
About this Dataset
Updated: 2024-02-22
Metadata Last Updated:
2019-08-27 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
N/A
| Title | RF Dataset of Incumbent Radar Systems in the 3.5 GHz CBRS Band |
|---|---|
| Description | The RF dataset can be used to develop and test detection algorithms for the 3.5 GHz CBRS or similar bands where the primary users of the band are federal incumbent radar systems. The dataset consists of synthetically generated radar waveforms with added white Gaussian noise. The RF dataset is suitable for development and testing of machine/deep learning detection algorithms. A large number of parameters of the waveforms are randomized across the dataset. Due to its large size, the dataset is divided into groups, and each group consists of multiple files. For more information about the dataset, refer to: R. Caromi, M. Souryal, and T. Hall "RF Dataset of Incumbent Radar Signals in the 3.5 GHz CBRS Band," J Res Natl Inst Stan 124:124038, 2019. available online at: https://doi.org/10.6028/jres.124.038. In addition, the metadata of the dataset is summarized in "Data Dictionary of 3.5 GHz Radar Waveforms" [pdf] accompanying the data. For more information about the motivation behind this RF dataset, refer to: T. Hall, R. Caromi, M. Souryal, and A. Wunderlich, "Reference Datasets for Training and Evaluating RF Signal Detection and Classification Models," in Proc. IEEE GLOBECOM Workshop on Advancements in Spectrum Sharing, Dec. 2019, available online at: https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928336. |
| Modified | 2019-08-27 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | 3.5 GHz; CBRS; incumbent radar detection; RF dataset; classification; deep learning; machine learning; spectrum sharing |
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