이종훈
Lee, JonghunDivision of Mobility Technology
학력
- 1998 ~ 2002성균관대학교 박사
- 1996 ~ 1998성균관대학교 석사
- 1992 ~ 1996성균관대학교 학사
경력
- 2007 ~ Current영남대학교 / 겸임교수
- 2005 ~ Current(재)대구경북과학기술연구원 / 선임 연구원
- 2002 ~ 2005삼성전자 방송통신연구소 / 책임
수상실적
- 2016 장관표창 / 미래창조과학부
- 2012 기타표창 / DGIST
- 2007 공로상 / DGIST
- 2006 우수논문상
- 1999 우수논문상
연구실 소개
- Advanced Radar Tech. Lab
-
The Department of Interdisplinary Engineering of DGIST has an opening for the graduate student with the following research focus area (Advisor: Prof. Jonghun Leen, Email: jhlee@dgist.ac.kr):1) radar processing (Deep/Mahcine Learning),
2) Automotive radar,
3) Vital Radar,
4) Sensor Fusion
Mission StatementsWe shall focus on making deep research on - unique, innovative and disruptive radar technology - radar application technology that has great industrial impact and is tightly linked to regional strategic industries - core breakthrough radar technology with significant depth, comprehensive academic achievements - defense and security radar technology that reflects publicity and improves people's lives according to Korean national demands - main research interests: Vehicle radar, biological radar, aviation and security radar, radar detection/identification and recognition technology, defense unmanned radar
Research Interests
Related Keyword
- "건물 붕괴 모델에서 GPR의 교차피크 신호 검출기반 시간 지연 추정기법 제안", 양경택. (2025-02). 건물 붕괴 모델에서 GPR의 교차피크 신호 검출기반 시간 지연 추정기법 제안. 한국산업정보학회논문지, 30(1), 27–40. doi: 10.9723/jksiis.2025.30.1.027
- "Resolution Improvement Algorithm with Two Targets Using Envelope of the Beat Signals for FMCW Radars", Kim, Bong-seok. (2025-01). Resolution Improvement Algorithm with Two Targets Using Envelope of the Beat Signals for FMCW Radars. IEEE Sensors Journal, 25(2), 3529–3537. doi: 10.1109/JSEN.2024.3505845
- "Super-Resolution Angle Estimation Algorithm using Low Complexity MUSIC-Based RELAX for MIMO FMCW Radar", Kim, Bong-Seok. (2025-01). Super-Resolution Angle Estimation Algorithm using Low Complexity MUSIC-Based RELAX for MIMO FMCW Radar. Journal of Electromagnetic Engineering and Science, 25(1), 41–53. doi: 10.26866/jees.2025.1.r.277
- "Sub-Terahertz Imaging-Based Real-Time Non-Destructive Inspection System for Estimating Water Activity and Foreign Matter Depth in Seaweed", Kwak, Dong-Hoon. (2024-12). Sub-Terahertz Imaging-Based Real-Time Non-Destructive Inspection System for Estimating Water Activity and Foreign Matter Depth in Seaweed. Sensors, 24(23). doi: 10.3390/s24237599
- "산업제조현장 스마트 안전 시스템용 레이다 및 IMU 센서를 이용한 앙상블 부스팅 모델 기반 작업자 탐지 기술", 송승언. (2024-10). 산업제조현장 스마트 안전 시스템용 레이다 및 IMU 센서를 이용한 앙상블 부스팅 모델 기반 작업자 탐지 기술. 한국산업정보학회논문지, 29(5), 21–32. doi: 10.9723/jksiis.2024.29.5.021
- "2D Spatial-Temporal Simulation of GPR Penetration in the 200-400MHz Band for Detecting Voids and Entrapped Persons in Multi-Layered Collapsed Building Structure", 2024 International Radar Conference, RADAR 2024, pp.1 - 4
- "Evaluating the Scalability of Soft Foreign Object Detection in Dry Foods Using Sub-Terahertz Radar and Deep-learning techniques", Song, Seungeon. (2024-09-06). Evaluating the Scalability of Soft Foreign Object Detection in Dry Foods Using Sub-Terahertz Radar and Deep-learning techniques. 49th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2024, 1–2. doi: 10.1109/IRMMW-THz60956.2024.10697861
- "MIMO Imaging Method with Extrapolation-Iterative Adaptive Approach-Based Super-Resolution Technique for Automotive Radar", Kim, Bong-Seok. (2024-05-09). MIMO Imaging Method with Extrapolation-Iterative Adaptive Approach-Based Super-Resolution Technique for Automotive Radar. 2024 IEEE Radar Conference, 1–6. doi: 10.1109/RadarConf2458775.2024.10549243
- "MIMO imaging method with iterative-based super-resolution for automotive radar", Kim, Bong-seok. (2024-04-19). MIMO imaging method with iterative-based super-resolution for automotive radar. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, 13031–13035. doi: 10.1109/ICASSP48485.2024.10447186
- "A lightweight deep-learning radar gesture recognition based on a structured pruning-NAS", Son, Eungang. (2023-10-13). A lightweight deep-learning radar gesture recognition based on a structured pruning-NAS. International Conference on Information and Communication Technology Convergence, ICTC 2023, 1729–1731. doi: 10.1109/ICTC58733.2023.10393376
연구 뉴스
- New Technology Doubles Resolution Without Radar Replacement Using Novel Algorithms! 2024-12-30
- 레이더 교체 없이, 새로운 알고리즘으로 해상도를 2배 높이는 신기술 개발! 2024-12-19
- One Stop Control System Detecting Down Bad Drones 2017-05-30
- Radar Specialist Dr. Dae-Gon Oh, Division of IoT and Robotics Convergence Research 2016-08-30
- The Nation’s First Dual Channel Super-resolution Radar Technology Developed in DGIST 2016-07-05
연구분야
미래유망 신기술(6T)
국가과학기술표준분류