{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T11:08:59Z","timestamp":1772363339976,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,8]],"date-time":"2018-11-08T00:00:00Z","timestamp":1541635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2016R1D1A3B03930798"],"award-info":[{"award-number":["NRF-2016R1D1A3B03930798"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010418","name":"Institute for Information and communications Technology Promotion","doi-asserted-by":"publisher","award":["2016-0-00564"],"award-info":[{"award-number":["2016-0-00564"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education, Korea (BK21 plus)","award":["21A20131600011"],"award-info":[{"award-number":["21A20131600011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s18113825","type":"journal-article","created":{"date-parts":[[2018,11,9]],"date-time":"2018-11-09T03:08:02Z","timestamp":1541732882000},"page":"3825","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System"],"prefix":"10.3390","volume":"18","author":[{"given":"Byeong Hak","family":"Kim","sequence":"first","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea"},{"name":"Hanwha Systems Corporation, Optronics Team, Gumi 39376, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7121-2746","authenticated-orcid":false,"given":"Danish","family":"Khan","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9015-2897","authenticated-orcid":false,"given":"Ciril","family":"Bohak","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Information Science, University of Ljubljana, SI-1000 Ljubljana, Slovenia"}]},{"given":"Wonju","family":"Choi","sequence":"additional","affiliation":[{"name":"Hanwha Systems Corporation, Optronics Team, Gumi 39376, Korea"}]},{"given":"Hyun Jeong","family":"Lee","sequence":"additional","affiliation":[{"name":"Agency for Defense Development, Yuseong, Daejeon 34186, Korea"}]},{"given":"Min Young","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea"},{"name":"Research Center for Neurosurgical Robotic System, Kyungpook National University, Daegu 41566, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1109\/MCOM.2018.1700455","article-title":"Detection, tracking, and interdiction for amateur drones","volume":"56","author":"Guvenc","year":"2018","journal-title":"IEEE Commun. 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