智能化无人机入侵检测与跟踪拦截系统设计与实现

近年来民用无人机领域发展迅猛，导致无人机“黑飞”事件频出，给国家安全及社会稳定带来了不小的挑战，迫切需要发展反无人机技术。对此，提出一种跟随式定向干扰方案，设计了一套基于视觉的无人机入侵检测与自动跟踪拦截系统。采用HOG+非线性SVM方案来识别无人机，加入ViBe运动目标检测算法来提高识别速度，并通过KCF算法实现无人机目标跟踪。设计制作无人机拦截系统的硬件设备主要包括跟踪伺服系统、底座和托盘等。实验表明，该系统的识别准确率达到90.54%，识别速度为20.56 fps，拦截平台能够在0.5 s内实现对目标无人机的瞄准，跟踪效果良好。在搭建的实物平台上进行系统测试，结果表明，该系统可实现对入侵无人机的运动检测、识别、跟踪与干扰，且识别准确率高，实时性好，能够对入侵的无人机进行自动拦截。

Design and implementation of intelligent UAV intrusion detection,tracking and interception system

In recent years, the field of civilian unmanned aerial vehicles has developed rapidly, leading to the frequent occurrence of unmanned aerial vehicle "black flying" incidents, which has brought considerable challenges to national security and social stability, and there is an urgent need to develop anti-UAV technology. In this regard, this paper proposes a follow-type directional jamming method and designs a vision-based UAV intrusion detection and automatic tracking and interception system. The HOG+nonlinear SVM scheme is used to identify the UAV, the ViBe moving target detection algorithm is added to improve the recognition speed, and UAV target tracking is realized through the KCF algorithm. Design and manufacture the hardware equipment of the UAV interception system, mainly including the tracking servo system, base and tray. Experiments show that the recognition accuracy of the system reaches 90.54%, the recognition speed is 20.56 fps, the interception platform can achieve the aim of the target UAV within 0.5 s, and the tracking effect is good. The system is tested on the built physical platform, and the results show that the system can realize the movement detection, recognition, tracking and interference of invading UAVs. The recognition accuracy is high, the real-time performance is good, and the system can automatically intercept the invading UAVs.