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Korea Society for Naval Science and Technology - Vol. 5 , No. 1

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Journal of the KNST - Vol. 5, No. 1, pp. 33-37
Abbreviation: KNST
ISSN: 2635-4926 (Print)
Print publication date 31 Mar 2022
Received 14 Dec 2021 Revised 04 Feb 2022 Accepted 08 Mar 2022
DOI: https://doi.org/10.31818/JKNST.2022.03.5.1.33
라이다를 활용한 드론 탐지체계 제안
김승운¹^{, *} ; 장호석²

1해군 소령/해군본부 정보화기획참모부 감시체계과

2해군 대령/해군본부 정보화기획참모부 감시체계과
Proposing a Drone Detection System Using LiDAR
Seung Woon Kim¹^{, *} ; Ho Seok Jang²
1LCDR/PIC of Force Support System Equipment, Surveillance System Division, DCNO for Information Planning, ROK Navy HQ

2CAPT/Chief of Surveillance System Division, DCNO for Information Planning, ROK Navy HQ

Correspondence to : ^*Seung Woon Kim PO Box No. 501-202 663, Gyeryongdae-ro Sindoan-myeon, Gyeryong-si, Chungcheongnam-do, 32800, Republic of Korea Tel: +82-42-553-5236 E-mail: swlycos@gmail.com
© 2022 Korea Society for Naval Science & Technology

초록

본 논문은 드론의 보편화로 인해 발생하는 군사적인 위협에 대응하기 위한 드론 탐지체계를 제안하는 것을 목적으로 한다. 드론의 기술 발전으로 많은 영역에서 드론이 활용되고 있지만, 목적에 따라 군사적 위협 또는 사회적 문제를 야기하고 있는 상황이다. 이러한 문제를 해결하기 위해 라이다, 레이더, 음향센서 등 다양한 센서를 이용하여 드론을 탐지하는 연구들을 조사하였고, 군 내 드론 탐지체계 현황을 확인함으로써 드론 탐지체계를 보완할 수 있는 방향을 살펴보았다. 이를 통해 라이다를 활용하여 드론 탐지체계를 구축하면 소형, 고속의 드론을 탐지하는 데 있어서 효과적일 것이며, 추후 레이더 등 기존의 탐지체계와도 병행하여 사용하면 발전하는 드론 기술에 신속히 대응할 수 있을 것으로 생각된다.

Abstract

Although drones are being used in many areas due to the technological development of drones, they are causing military threats or social problems depending on the purpose. In order to solve this problem, researches on detecting drones using various sensors such as lidar, radar, and acoustic sensors were investigated, and directions for supplementing the drone detection system were examined by checking the status of drone detection systems in the military. Building a drone detection system using lidar will be effective in detecting small and high-speed drones. And if it is used in parallel with existing detection systems such as radar in the future, it is thought that it will be possible to respond quickly to the evolving drone technology.


Keywords: Drone Detection, LiDAR, Drone, Drone Threat, Surveillance 키워드: 드론 탐지, 라이다, 드론, 드론 위협, 감시

Acknowledgments

이 논문은 2021년도 한국해군과학기술학회 동계학술대회 발표 논문임.

References


1.	Dinesh Sathyamoorthy, "A Review of Security Threats of Unmanned Aerial Vehicles and Mitigation Steps", The Journal of Defense and Security, Vol. 6, No. 1, 2015, pp. 81-97.
2.	Kang, S. W., “A history of drone attacks older than 100 years“, The Seoul Economic Daily, 2019.
3.	Cha, D., Park, J., Son, C., Park, Y., Kim, K., “Current status of military drones and countermeasures against drones,” MONTHLY Defense & Technology, Vol. 471, 2018, pp. 140-153.
4.	Moon, M., Song, K., Yu, S., Sim, H., Lee, W., “Research on the drone detection based on the radar”, Journal of Satellite, Information and Communications, Vol. 12, No. 2, 2017, pp. 99-103.
5.	Lee, K. W., Song, K. M., Song, J. H., Jung, C. H., Lee, W. K, Lee, M. J., Song, Y. K., “Implementation of Radar Drone Detection Based on ISAR Technique”, The Journal of Korean Institute of Electromagnetic Engineering And Science, Vol. 28, No. 2, 2017, pp. 159-162.
6.	Lauerenzis, M., Hengy, S., Hommes, A., Kloeppel, F., Shoykhetbrod, Alex., Geibig, T., Johannes, W., Naz, P., Christnacher, F., "Multi-sensor field trials for detection and tracking of multiple small unmanned aerial vehicles flying at low altitude", Proc. of SPIE, Vol. 10200, 2017, pp. 102001A-1 - 102001A-13.
7.	Nguyen, P., Truong, H., Ravindranathan, M., Nguyen, A., Han, R., Vu, T., "Cost-Effective and Passive RF-Based Drone Presence Detection and Characterization", GetMobile Mobile Computing and Communications, Vol. 21, No. 4, 2017, pp. 30-34.
8.	Allahham, M. S., Al-Sa’d, M. F., Al-Ali, A., Mohamed A., Khattab, T., Erbad, A., "RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database", Future Generation Computer Systems, Vol. 100, 2019, pp. 86-97.
9.	Yi, K. W., Seo, K., “Image Based Identification and Localizing of Drones”, The Transactions of the Korean Institute of Electrical Engineers, Vol. 69, No. 2, 2020, pp. 331-336.
*10.*	Lee, H., Shim, D. H., “Research of the Learning-based Detection and Tracking the Drone using the monocular camera”, The Korean Society for Aeronautical & Space Sciences, 2017, pp. 904-905.
*11.*	Yoo, S., Ryu, Y., Shin, S., Oh, H., “Analysis of commercial drone sounds and its identification”, Information and Control Symposium, 2020, pp. 493-494.
*12.*	Hammer, M., Hebel, M., Laurenzis, M., Arens, M., "LiDAR-based detection and tracking of small UAVs" Proc. of SPIE, Vol. 10799, 2018, pp. 107990S-1 - 107990S-9.
*13.*	Church, P., Grebe, C., Matheson, J., Owens, B., "Aerial and surface security applications using LiDAR", Proc. of SPIE 10636, 2018, pp. 1063604-1 – 1063604-12.
*14.*	https://www.amazon.com/Amazon-Prime-Air
*15.*	https://www.dji.com/kr/newsroom/dji-introduces-new-m200-series
*16.*	https://twitter.com/aerones_com/status/820934832461148160
*17.*	https://www.rda.go.kr:2360/board/board.do?mode=view&prgId=day_ppemoventEntry&dataNo=100000749205
*18.*	https://itbiznews.com/news/articleView.html?idxno=25399
*19.*	https://www.neptectechnologies.com/security-lidar
*20.*	https://www.youtube.com/watch?v=p56GJlI48kE