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Baseline Deep Learning Detectors for Radar Detection in the 3.5 GHz CBRS Band

This project aims to create a comprehensive framework for generating radio frequency (RF) datasets, designing deep learning (DL) detectors, and evaluating their detection performance using both simulated and experimental test data. The proposed tools and techniques are developed in the context of dynamic spectrum use for the 3.5 GHz Citizens Broadband Radio Service (CBRS), but they can be utilized and expanded for standardization of machine learned spectrum awareness technologies and methods. This dataset consists of pre-trained DL models for radar detection in the CBRS band using simulated waveforms. The code for creating and using these models is available at https://github.com/usnistgov/BaselineDeepLearningRadarDetectors.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2021-03-01
Date Created: N/A
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Data Provided by:
3.5 GHz; CBRS; radar; detection; deep learning; radio frequency signals; spectrum; MLSA
Dataset Owner: N/A

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Title Baseline Deep Learning Detectors for Radar Detection in the 3.5 GHz CBRS Band
Description This project aims to create a comprehensive framework for generating radio frequency (RF) datasets, designing deep learning (DL) detectors, and evaluating their detection performance using both simulated and experimental test data. The proposed tools and techniques are developed in the context of dynamic spectrum use for the 3.5 GHz Citizens Broadband Radio Service (CBRS), but they can be utilized and expanded for standardization of machine learned spectrum awareness technologies and methods. This dataset consists of pre-trained DL models for radar detection in the CBRS band using simulated waveforms. The code for creating and using these models is available at https://github.com/usnistgov/BaselineDeepLearningRadarDetectors.
Modified N/A
Publisher Name National Institute of Standards and Technology
Contact mailto:raied.caromi@nist.gov
Keywords 3.5 GHz; CBRS; radar; detection; deep learning; radio frequency signals; spectrum; MLSA
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}

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