DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Park, Seong-Ook | - |
dc.contributor.advisor | 박성욱 | - |
dc.contributor.author | Kim, Do-Hoon | - |
dc.date.accessioned | 2019-09-04T02:41:44Z | - |
dc.date.available | 2019-09-04T02:41:44Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843372&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266788 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.2,[v, 47 p. :] | - |
dc.description.abstract | Recently, drones have become a new risk factor for society due to irresponsible flight. It is important to prevent the drones from creating dangerous situations. In this thesis, we proposed a pulse radar system for detecting drone. Since the manufactured radar system transmits fully synchronized signals, it can accurately measure the speed and distance of the object, and the performance is verified by actual drone experiment. In addition, We also proposed a deep-learning method for classifying drones using radar signals reflected on drones. We propose a new deep-learning network structure that solves the problems of existing techniques using spectrograms and verify the performance by classifying the drone using the detected drone signal | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Drone classification▼adrone detection▼apulse radar▼adeep learning▼aconvolutional neural network | - |
dc.subject | 드론 탐지▼a드론 식별▼a펄스 레이더▼a딥러닝▼a스펙트로그램 | - |
dc.title | Pulse radar system design for drone detection and deep learning using raw radar data for drone classification | - |
dc.title.alternative | 드론 탐지를 위한 Pulse 레이더 시스템 설계 및 Raw 레이더 데이터와 딥러닝을 이용한 드론 식별 기법 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 김도훈 | - |
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