HollowBox: An anchor‐free UAV detection method

Abstract

Abstract Unmanned aerial vehicles (UAV) “black flight” incidents cause serious security risks and economic losses to airports. Additionally, existing UAV detection methods are mainly radar technology at airports. Whereas, it is unable to correctly identify the number of UAVs and visualise their size, which undoubtedly poses a serious security risk. Accordingly, an anchor‐free UAV detection method HollowBox is proposed to supplement radar detection equipment for the airport “black flight” problem. It is inspired by the FoveaBox object detection method, the object detection feature layers are reset and the allocation ratio of positive and negative samples in the training phase are redefined, the HollowBox UAV detection is proposed according to the multi‐size characteristics. Extensive experiments show that, the approach achieves 90.1% AP, 6% false detection rate and 17.2 FPS inference speed, which accomplished a satisfactory performance, as verified by the real‐shot data collected of an airport in Tianjin. This work is of great significance for the application in airport UAV detection.