基于射频的无人机检测和机器学习分类技术

Mariam M. Alaboudi, M. A. Talib, Q. Nasir
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引用次数: 2

摘要

这篇研究论文提供了一个全面的调查综述无人机检测使用射频(RF)为基础的技术以及机器学习和定位算法。射频信号证明了其在检测无人机方面的有效性,然而,由于缺乏公开的调查,本研究论文通过解决实施方法并讨论在测试环境,检测范围和系统准确性方面获得的结果,回顾了新出现的基于射频的技术。在本次调查综述中,收集了30篇会议和期刊论文,但由于论文的贡献和有限的篇幅,仅对部分论文进行了讨论。最后,本调查还讨论了无人机使用射频检测遇到的挑战,因为它对系统的效率有很大的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radio Frequency-based Techniques of Drone Detection and Classification using Machine Learning
This research paper provides a comprehensive survey review on drone detection using Radio Frequency (RF)-based techniques along with machine learning and localization algorithms. RF signals proved its effectiveness in detecting drones, however, due to the lack of a published survey, this research paper reviews the newly emerged RF-based techniques by addressing the implemented methods and discussing the results obtained in terms of the testing environment, range of detection and accuracy of the system. In this survey review, thirty conference and journal papers have been collected, however only selected papers have been discussed depending on the contribution and limited space of the paper. Finally, this survey also discusses the challenges encountered in drone detection using RF due to its great impact on the efficiency of the system.
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