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作 者:马越[1] 缪晨[1] 张若愚 王晶琦[1] 吴文[1] MA Yue;MIAO Chen;ZHANG Ruoyu;WANG Jingqi;WU Wen(Key Laboratory of Near-Range RF Sensing ICs and Microsystems,Ministry of Education,Nanjing University of Science and Technology,Nanjing 210094,China)
机构地区:[1]南京理工大学近程射频感知芯片与微系统教育部重点实验室,江苏南京210094
出 处:《国防科技》2023年第5期60-66,共7页National Defense Technology
基 金:国家自然科学基金项目(61671241、62071235、62071440、62101258、62271260、62201266)。
摘 要:小型无人机的雷达截面较小,对它实施远距离探测难度较大,且环境因素和误报问题也会影响雷达探测的表现。然而,雷达探测仍是最前沿的无人机探测技术之一。探讨无人机雷达探测系统在探测和追踪无人机方面的应用和挑战。介绍无人机雷达探测系统的基本原理和研究热点,详细分析无人机雷达探测系统在探测和追踪无人机方面的效果以及遇到的性能和技术上的挑战。未来的研究可以使用合成孔径雷达和集成多个传感器的方法来进一步提高雷达探测系统的探测性能并减少误报数量。同时,机器学习和人工智能技术的应用也可能有助于提高探测精度,使雷达系统适应不同的环境和目标。Radars have difficulty detecting small drones at long distances due to their small cross-section,and radar-based drone detection is susceptible to environmental factors and false reports.Nonetheless,radar remains a cutting-edge technology for drone detection.In this work,the application of radar systems to drone detection and tracking is discussed,as well as the challenges facing these applications.The basic principles and research highlights of radar-based drone detection are introduced,along with their relationship to the broader field of drone detection.A detailed analysis is conducted on the effectiveness of radar-based drone detection and tracking systems,covering the performance and technical challenges that they face,thereby suggesting that in the future,synthetic aperture radar(SAR)be combined with multiple multi-sensor methods to improve detection performance and reduce false reports.Other recommendations include the use of machine learning and artificial intelligence to improve detection accuracy and adapt radar systems to different environments and targets.In summary,advancements in these technologies will lead to even more effective and reliable drone detection systems.
分 类 号:TN957.51[电子电信—信号与信息处理] E927[电子电信—信息与通信工程]
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