V-RBNN based small drone detection in augmented datasets for 3D LADAR system

Kim, Byeong Hak (author), Khan, Danish (author), Bohak, Ciril (author), Choi, Wonju (author), Lee, Hyun Jeong (author), Kim, Min Young (author)

A 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.

• Language: English
• Keywords: drone detection, clustering, 3D sensor, LiDAR, fusion data, 3D LADAR
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2018
• Number of pages: 16 str.
• Numbering: Vol. 18, iss. 11, art. 3825
• PID: 20.500.12556/RUL-132014
• UDC: 004
• ISSN on article: 1424-8220
• DOI: 10.3390/s18113825
• COBISS.SI-ID: 1538015427
• Publication date in RUL: 08.10.2021

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 08.11.2018

Secondary language

• Language: Slovenian
• Keywords: detekcija dronov, gručenje, 3D senzor, LiDAR, zlivanje podatkov, 3D LADAR