区域生长在跑道异物检测中的应用

Application of regional growth in runway foreign object detection

机场跑道异物检测是保障机场及飞行器安全的重要内容,针对边灯式FOD雷达在杂波区域常规检测算法异物检测能力差的问题,文章提出了一种基于图像的区域生长杂波区域目标提取算法。文章首先分析了区域生长方法的原理和生长流程;其次,通过仿真验证了区域生长方法对特征区域提取的有效性;最后,将区域生长方法应用到跑道雷达异物检测中。实测试验结果表明,该方法能够有效抑制雷达杂波区域的虚假目标,降低机场跑道异物(FOD)检测系统虚警,提高雷达目标发现能力。

Foreign object detection on airport runways is an important part of ensuring the safety of airports and aircraft.Aiming at the problem that the conventional detection algorithm of edge-light FOD radar in the clutter region has poor foreign object detection ability,an image-based region growing clutter region target extraction algorithm is proposed.Firstly,the principle of the region growing method and its growth process are analyzed,and then the effectiveness of the region growing method for extracting characteristic regions is verified by simulation.Finally,the region growing method is applied to the foreign object detection of runway radar.The actual test results show that the method can effectively Suppress false targets in radar clutter areas,reduce false alarms of foreign object detection(FOD)systems on airport runways,and improve radar target detection capabilities.