Onboard far-field aircraft detection is needed for safe non-cooperative traffic mitigation in autonomous small unmanned aerial system (sUAS) operations. Machine vision systems, based on standard optics and visible light detectors, possess the ideal size, weight, and power (SWaP) requirements for sUAS. This work presents the design and analysis of a novel aircraft detection and tracking pipeline based on optical sensing alone. Key contributions of the work include a refined range inequality model based on sensing and detection with Federal Aviation Administration well-clear separation assurance distances between aircraft in mind, a detector fusion method to maximize the benefit of two image detectors, and a comparative analysis of linear Kalman filtering and extended Kalman filtering to seek optimal tracking performance. The pipeline is evaluated offline against multiple intruder platforms, using two types of flight encounters: multirotor sUAS versus fixed-wing sUAS and multirotor sUAS versus general aviation (GA) plane. Analysis is restricted to the rate-limiting head-on and departing collision volume cases vertically separated for safety. Results indicate that it is feasible to use the proposed optical spatial-temporal tracking algorithm to provide adequate alerting time to prevent penetration of well-clear separation volumes for both sUAS and GA aircraft.

为了在自主小型无人航空系统（sUAS）操作中安全地缓解非合作交通，需要机载远场飞机检测。基于标准光学器件和可见光检测器的机器视觉系统具有sUAS的理想尺寸，重量和功率（SWaP）要求。这项工作提出了一种仅基于光学传感的新型飞机检测和跟踪管道的设计和分析。这项工作的主要贡献包括：基于传感和检测的精确范围不等式模型，并牢记飞机之间的清晰间隔保证距离；一种探测器融合方法，可最大程度地利用两个图像探测器的优势；对线性探测器进行比较分析。卡尔曼滤波和扩展卡尔曼滤波以寻求最佳跟踪性能。使用两种类型的飞行遭遇，对多个入侵者平台进行离线评估：多旋翼sUAS与固定翼sUAS和多旋翼sUAS与通用航空（GA）飞机。为了安全起见，分析仅限于垂直分开的限速正面和离开碰撞量情况下进行。结果表明，使用拟议的光学时空跟踪算法来提供足够的警报时间以防止sUAS和GA飞机穿透清晰的分隔体积是可行的。