Abstract: With the great development of general aviation and rotor unmanned aerial vehicle, the urgent need is to guarantee the safety of airspace monitoring and management. Since radar has a wide tracking-blind area in low-airspace, radar echo will be disturbed easily by cluster waves which result in exception of the target information gathering. Large-scale arrangement of ADS-B system also has a limitation, thus research on low-airspace surveillance and management has been a hot topic nowadays. Here, a radar/visible light monitoring and tracking method is proposed, which targeting the rotorcraft in low-altitude airspace. Based on the framework of Tracking-Learning-Detecting（TLD）, the radar is set as main tracker and visible light sensor as detector. Measurement model switching and data online update can be completed through interactive multi-model method and PN-learning process, while making the target state information and monitoring/tracking system more accurate. The availability has been verified by results of numerical simulation.

Key words: airspace surveillance, radar, visible light sensor, Tracking-Learning-Detecting（TLD）, target tracking

摘要： 近年来，随着通用航空和旋翼无人机的飞速发展，对相关空域的安全性监视与管理提出了迫切要求。由于雷达在低空空域存在探测盲区，极易受到杂波干扰，无法准确获取目标信息，而ADS-B系统大规模布设存在局限性，低空空域的有效监视与管理成为研究的热点。研究了一种低空目标的雷达/可见光协同监视跟踪方法，该方法基于跟踪-学习-检测（TLD）架构，将雷达作为主跟踪器，可见光传感器作为检测器，通过交互多模型算法和学习器实现量测模型切换和数据在线更新，从而获取更准确的目标状态信息，实现低空空域更精确的监视和目标跟踪，数据仿真说明了该方法的有效性。

关键词: 空域监视, 雷达, 可见光传感器, 跟踪-学习-检测, 协同跟踪