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近年来，无人机在各个领域得到广泛应用，但越来越多的无人机也带来了一系列隐私和安全问题。因此，对无人机的检测和管理变得至关重要，目前通过射频指纹识别无人机的方法取得了较大进展。在结合国内外大量研究成果的基础上，对无人机射频指纹系统的各个步骤进行深入探讨。分析了各种无人机识别技术的优缺点，并详细阐述了无人机通信方式和射频指纹的形成机理与特性。根据信号收集、预处理、特征提取和分类识别4个阶段，对无人机射频指纹系统的相关技术进行了系统梳理，讨论了无人机射频指纹系统性能评估方法。对当前无人机射频指纹研究现状进行了问题分析与展望，包括射频指纹数据集缺乏、射频指纹稳定性、射频指纹的唯一性以及深度学习在射频指纹应用领域的探索，并进行了全文总结。
Abstract：In recent years, drones have been widely used in various fields, but the increasing drones also brings a series of privacy and security issues. Therefore, the detection and management of drones has become very important, and the method of identifying drones through radio frequency fingerprints has made great progress. On the basis of a large number of research results at home and abroad, the various steps of the UAV radio frequency fingerprint system are discussed in depth. Firstly, the advantages and disadvantages of various UAV identification technologies are analyzed, and the communication mode of UAVs and the formation mechanism and characteristics of radio frequency fingerprints are elaborated. Then, according to the four stages of signal collection, preprocessing, feature extraction and classification recognition, the related technologies of the UAV radio frequency fingerprint system are systematically sorted out, and the performance evaluation method of the UAV radio frequency fingerprint system is briefly discussed. The current situation of UAV radio frequency fingerprint research is analyzed and prospected, including the lack of RF fingerprint datasets, the stability of radio frequency fingerprints, the uniqueness of radio frequency fingerprints, and the exploration of deep learning in the field of radio frequency fingerpri nt applications. Finally, a full-text summary is given.
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基本信息:
DOI：
中图分类号:TP391.44;V279
引用信息:
[1]王豪,罗俊松,王惠明等.无人机射频指纹识别方法综述[J].无线电工程,2024,54(11):2672-2684.
基金信息:
四川省国际科技创新合作/港澳台科技创新合作项目(2023YFH0092); 四川省区域创新合作项目(2022YFQ0017); 国家自然科学基金(62172060)~~