机场跑道异物检测系统能够快速精确地检测和识别跑道异物,对于保障机场飞行安全意义重大。针对单一传感器探测系统表现出的弊端,文中提出结合小型高分辨率毫米波雷达和高清夜视摄像机的新型系统方案,发挥多传感器数据融合的优势,获取机场跑道异物多种特征信息。并重点探讨了数据处理分系统在目标检测模块中采用的自适应双阈值Canny 边缘检测、混合高斯模型背景建模、局部阈值背景减除等算法,有效提高机场跑道异物检测的效率和精度。

The foreign object debris (FOD) detection and surveillance system for airport runway can detect and identify the FOD quickly and accurately, which has great significance for ensuring the flight safety in the airport. To solve the shortcomings of the single-sensor detection system, a new system which combining small high-resolution millimeter-wave radar and high-definition night vision camera, and developing the advantage of merging data of multisensor to obtain more characteristic information of FOD on airport runways is proposed in this paper. In addition, the adaptive dual-threshold Canny edge detection, Gaussian mixture model background construction and local threshold background subtraction algorithms used in the target detection module of the data processing sub-system is mainly discussed in this paper. The efficiency and accuracy of FOD detection for airport runway can be improved effectively by this system.

TN958.3