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DroneRFa丨A Large-scale Dataset of Drone Radio Frequency Signals for Detecting Low-altitude Drones|无人机检测数据集|无线电频率信号分析数据集
收藏DataCite Commons2025-04-27 更新2025-05-18 收录
下载链接：
https://www.scidb.cn/detail?dataSetId=34f0a91e8a544904998b8fdc44477380
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DroneRFa: A Large-scale Dataset of Drone Radio Frequency Signals for Detecting Low-altitude DronesYU Ningning1 , MAO Shengjian1 , ZHOU Chengwei1 , SUN Guowei3 , SHI Zhiguo1 , CHEN Jiming1, 21.Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province, Zhejiang University, Hangzhou 310027, China2.College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China3.Chengde City’s Police Department of Hebei Province, Chengde 067000, ChinaA large-scale dataset of drone radio frequency signals, namely DroneRFa, is constructed to research and develop anti-drone detection and recognition technologies. This dataset uses a software-defined radio device to monitor communication signals between drones and their controllers, including 9 types of flying drone signals in an outdoor environment, 15 types of drone signals in an indoor environment, and 1 type of background signal as a reference. Each type of data has no less than 12 segments, each containing more than 100 million sampling points. The data acquisition covered three Industrial Scientific Medical (ISM) radio bands, and recorded the multifrequency communication activity of drones. The dataset has detailed flying distance and communication frequency band labeling, which are represented with prefix characters and binary codes to facilitate easy access to specific data required by users. Furthermore, this paper proposes two drone identification schemes based on spectral and visual statistical features and deep learning representation to verify the reliability and validity of the dataset.Citation: YU Ningning, MAO Shengjian, ZHOU Chengwei, SUN Guowei, SHI Zhiguo, CHEN Jiming. DroneRFa: A Large-scale Dataset of Drone Radio Frequency Signals for Detecting Low-altitude Drones[J]. Journal of Electronics & Information Technology. 2024, 46(4): 1147-1156. doi: 10.11999/JEIT230570 URL：https://jeit.ac.cn/cn/article/doi/10.11999/JEIT230570
提供机构：
Science Data Bank
创建时间：
2024-12-31
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