V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System
AbstractA common countermeasure to detect threatening drones is the electro-optical infrared (EO/IR) system. However, its performance is drastically reduced in conditions of complex background, saturation and light reflection. 3D laser sensor LiDAR is used to overcome the problems of 2D sensors like EO/IR, but it is not enough to detect small drones at a very long distance because of low laser energy and resolution. To solve this problem, A 3D LADAR sensor is under development. In this work, we study the detection methodology adequate to the LADAR sensor which can detect small drones at up to 2 km. First, a data augmentation method is proposed to generate a virtual target considering the laser beam and scanning characteristics, and to augment it with the actual LADAR sensor data for various kinds of tests before full hardware system developed. Second, a detection algorithm is proposed to detect drones using voxel-based background subtraction and variable radially bounded nearest neighbor (V-RBNN) method. The results show that 0.2 m L2 distance and 60% expected average overlap (EAO) indexes are satisfied for the required specification to detect 0.3 m size of small drones. View Full-Text
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Kim, B.H.; Khan, D.; Bohak, C.; Choi, W.; Lee, H.J.; Kim, M.Y. V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System. Sensors 2018, 18, 3825.
Kim BH, Khan D, Bohak C, Choi W, Lee HJ, Kim MY. V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System. Sensors. 2018; 18(11):3825.Chicago/Turabian Style
Kim, Byeong H.; Khan, Danish; Bohak, Ciril; Choi, Wonju; Lee, Hyun J.; Kim, Min Y. 2018. "V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System." Sensors 18, no. 11: 3825.
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