Seung-Hyun Kong 

연구분야 > 지능형 모빌리티 기술 (en)연구분야 > 친환경 모빌리티 기술전임교수 (en)

Office

F412

Tel

1265

Summary

Research Interest

Advanced Reinforcement Learning for Self-Driving, Deep Learning for Vehicle Sensors (LiDAR, Radar, Camera, GNSS), Deep Learning for Sensor Fusion for Localization and Reliable Perception, Cooperative Vehicle Navigation for Urban Environments, Assisted-GNSS for Mobile and V2X Communication Systems, Wireless Fingerprint

Education

  • Ph.D. in Aeronautics and Astronautics, Stanford Univ., CA, 1995-1996, 2005 “Advancements in Mobile Positioning Technologies and Mobile Location Networks”
  • M.S. in Electrical Engineering, Polytechnic Univ. (merged to NYU), NY, 1994
  • B.S. in Electronics Engineering, Sogang University, Seoul, Korea, 1988-1991

Biography

Prof. Seung-Hyun Kong (2016~IEEE Senior Member) received B.S. degree in Electronics Engineering from Sogang University, Korea, in 1992, M.S. degree in Electrical Engineering from Polytechnic University, New York, in 1994, and Ph.D. degree in Aeronautics and Astronautics from Stanford University, CA, in Jan. 2006. From 1997 to 2004 and from 2006 to 2010, he was with the industry including Samsung Electronics (Telecommunication Research Center), Korea, and Qualcomm (Corporate R&D Department), San Diego, USA, where he was involved with advanced R&D projects in mobile communication systems, wireless positioning, and assisted GNSS. Since 2010, he is with Korea Advanced Institute of Science and Technology (KAIST), where he is currently an associate professor at the CCS Graduate School of Mobility. He has led multiple national and industry projects related to the development of robust GNSS and navigation techniques, deep learning techniques for autonomous vehicle systems, and digital transportation infra-systems of Korea for autonomous vehicles. His research interests include vehicular localization, GNSS, and navigation techniques, deep learning techniques for vehicle sensors and sensor fusion, autonomous vehicles, and vehicular communication systems (V2X). He has authored more than 100 papers in peer-reviewed journals and conference proceedings and 12 patents. He won the KAIST Innovation Technology Award in 2015, and his self-driving car research group won the President Prize (of Korea) in the 2018 International Student Autonomous Driving competition held in Daegu, Korea. He has been the team leader of BK21+ Future Transportation Research team since 2014, and he has served as a program chair and an organization chair of multiple conferences in Korea and a program co-chair of IEEE ITSC2019 in New Zealand. He served as the lead guest editor of the IEEE T-ITS special issue on “ITS empowered by AI technologies” and the IEEE Access special section on “GNSS, Localization, and Navigation Technologies”. He serves as an editor of IEEE T-ITS and is organizing committees for IEEE IV 2024 in Jeju Korea.

Publication

INTERNATIONAL PUBLICATIONS (*: corresponding author)

REspected journals and magazines

  1. S.-H. Kong*, S. Cho, S.-T. Han, and E. Kim*, “GPS First Arrival Path Detection Network using MLP-Mixer,” IEEE Trans. on Wireless Communications, March. 2022.
  2. Seok-Teak Yun and Seung-Hyun Kong*, “Data Driven In-orbit Current and Voltage Prediction Using Bi-LSTM for LEO Satellite Lithium-Ion Battery SOC Estimation”, IEEE Trans. on Aerospace and Electronic Systems, (SCI, IF 4.102, Accepted in Apr. 2021)
  3. Seok-Teak Yun and Seung-Hyun Kong*, “Forecasting Methods of Battery Charge and Discharge Current Profile for LEO Satellites”, Electronics, Vol. 10, No. 23, Dec. 2021. (SCIE, IF 3.022)
  4. S.-H. Kong, I Made Aswin Nahrendra, Dong-Hee Paek, “Enhanced Off-Policy Reinforcement Learning with Focused Experience Replay,” IEEE Access, vol. 9, pp. 93152-93164, May 2021.
  5. Seok-Teak Yun and Seung-Hyun Kong*, “Design of High Efficiency Controller for Wide Input Range DC-DC Piezoelectric Transformer Converter”, IEEE Access, Dec. 2020.
  6. M.-L. Hoang, M.-J. Kim, and S.-H. Kong*, “Automatic Recognition of General LPI Radar Waveform using SSD,” IEEE Trans. on Signal Processing, vol. 67, no. 13, pp. 3516-3530, 2019 (SCI, IF 5.25, JCR Top 9.31%)
  7. S.-H. Kong*, M. Kim, and L. Hoang, “Automatic LPI Radar Waveform Classification Technique Using CNN,” IEEE Access, vol. 6, pp. 4207-4219, 2018 (SCIE, IF 3.557)
  8. Y.-J. Choi, J.-Y. Lee, and S.-H. Kong*, “Design and Performance Evaluation of Textile-based Electrodes for Steering Wheel Cover to Acquire ECG Signals,” IEEE Access, vol. 6, pp. 415-427, 2018 (SCIE, IF 3.557)
  9. S.-H. Kong* and S.-Y. Jun, “Cooperative Positioning Technique with Decentralized Malicious Vehicle Detection,” IEEE Trans. on Intelligent Transportation Systems, vol. 19, no. 3, pp.826-838, 2018 (SCI, IF 4.051, JCR Top 4.8%)
  10. H. Ko, Y. Shim, and S.-H. Kong*, “Realization and Demonstration of Enhanced Korean High-Speed Train Navigation System with Noise Filtering Schemes,” International Journal of Control, Automation, and Systems, IJCAS, Vol. 6, No. 2, pp. 769-781, 2018. (SCI, IF 2.173)
  11. K. H. Kim, S. H. Seol, and S.-H. Kong*, “High-Speed Train Navigation System based on Multisensor Data Fusion and Map Matching Algorithm,” International Journal of Control, Automation, and Systems, IJCAS, vol.  13,  no. 3, pp. 503-512, June 2015. (SCI, IF 1.219)
  12. S.-H. Kong*, “High Sensitivity and Fast Acquisition Technologies for GNSS Receivers,” IEEE Signal Processing Magazine, vol. 34, no. 5, pp. 59-71, 2017. (SCI, IF 9.654, JCR Top 1.54%)
  13. Y.-J. Choi, J.-Y. Lee, and S.-H. Kong*, “Driver ECG Measuring System with a Conductive Fabric-Based Dry Electrode,” IEEE Access, vol. 6. pp. 415-427, 2018. (SCIE, IF 3.244, JCR Top 20.77%]
  14.  Y.-J. Choi, S. I. Han, S.-H. Kong*, and H.  Ko,  “Driver  Status  Monitoring Systems for Smart Vehicles using Physiological Signals,” IEEE Signal Processing Magazine, vol. 33, no. 6, pp. 22-34, 2016. (SCI, IF 6.671, JCR Top 1.54%)
  15. S.-H. Kong* and B. Kim, “Error Analysis of the OTDOA from the Resolved First Arrival Path in LTE,”  IEEE Trans.  on Wireless Communications, vol. 15, no. 10, pp. 6598-6610, 2016. (SCI, IF 2.925, JCR Top 7.31%)
  16.  B. Kim and S.-H. Kong*, “A Novel Indoor Positioning Technique Using Magnetic Fingerprint Difference,” IEEE Trans. on Instrumentation and Measurements, vol. 65, no. 9, pp. 2035-2045 , March 2016 (SCI, IF 1.808, JCR Top 24.14%)
  17.  H. Ko, B. Kim, and S.-H. Kong*, “GNSS Multipath Resistant Cooperative Navigation in Urban Vehicular Networks,” IEEE Trans. on Vehicular Technology, vol. 64, no. 12, pp. 5450-5463, Dec. 2015. (SCI, IF 1.978, JCR Top 17.07%)
  18. B. Kim and S.-H. Kong*, “Low Computational Enhancement of STFT-based Parameter Estimation,” IEEE Journal of Selected Topics in Signal Processing, J-STSP, vol. 9, no. 8, pp. 1610-1619, Dec. 2015. (SCI, IF 2.373, JCR Top 14.4%)
  19. K. H. Kim and S.-H. Kong*, “Slip and Slide Detection and Adaptive Information Sharing Algorithms for High-Speed Train Navigation System,” IEEE Trans. on Intelligent Transportation Systems,  vol.  16,  no.  6,  pp.  3193- 3204, Dec. 2015. (SCI, IF 2.377, JCR Top 6.35%)
  20. S.-H. Kong*, “SDHT for Fast Detection of Weak GNSS Signals,” IEEE Journal on Selected Areas in Communications, JSAC, vol. 33, no. 11, pp. 2366- 2378, May 2015. (SCI, IF 3.453, JCR Top 6.23%)
  21. S.-H. Kong*, “Fast Multi-Satellite ML Acquisition for A-GPS,”  IEEE Trans. on Wireless Communications, vol. 13, no. 9, pp. 4935-4946, Sep. 2014. (SCI, IF2.762, JCR Top 13.25%)
  22. S.-H. Kong*, “Analysis of Code Phase Estimation Error from the Resolved  First Arrival Path,” IEEE Trans. on Aerospace and Electronic Systems, vol. 50, no. 4, pp. 2456-2467, Oct. 2014. (SCI, IF 1.394, JCR Top 6.67%)
  23. B. Kim and S.-H. Kong*, “Two-Dimensional Compressed Correlator for Fast acquisition of BOC(m,n) Signals,” IEEE Trans. on Vehicular Technology,  vol. 63, no. 6, pp. 2662-2672, Jul. 2014. (SCI, IF 2.642, JCR Top 19.48%)
  24. B. Kim and S.-H. Kong*, “Design of FFT-based TDCC for GNSS Acquisition,” IEEE Trans. on Wireless Communications, vol. 13, no. 5, pp.  2798- 2808, May 2014. (SCI, IF 2.732, JCR Top 13.25%)
  25. B. Kim and S.-H. Kong*, “Determination of Detection Parameters on TDCC Performance,”  IEEE Trans. on Wireless Communications,  vol. 13,  no. 5, pp. 2422-2431, May 2014. (SCI, IF 2.762, JCR Top 13.25%)
  26. S.-H. Kong* and B. Kim, “Two-Dimensional Compressed Correlator for Fast PN Code Acquisition,” IEEE Trans. on Wireless Communications, vol.  12, no. 11, pp. 5859-5867, Nov. 2013. (SCI, IF 2.418, JCR Top 13.77%)
  27. W. Nam and S.-H. Kong*, “Least-Squares-Based Iterative Multipath Super-Resolution Technique,” IEEE Trans. on Signal Processing, vol.  61, no.  3, pp. 519-529, Feb. 2013. (SCI, IF 2.813, JCR Top 9.31%)
  28. S.-H. Kong*, “A Deterministic Compressed GNSS Acquisition Technique,” IEEE Trans. on Vehicular Technology, vol. 62, no. 2, pp. 511-521, Feb. 2013. (SCI, IF 2.063, JCR Top 12.82%)
  29. S.-H. Kong*, “Statistical Analysis of Urban GPS Multipaths and  Pseudo Range Measurement Errors,” IEEE Trans. on Aerospace and Electronic Systems, vol. 47, no. 2, pp. 1101-1113, Apr. 2011. (SCI, IF 0.917, JCR Top 14.81%)
  30. S.-H. Kong* and W. Nam, “A-GNSS Sensitivity for Parallel Acquisition in Asynchronous Cellular Networks,” IEEE Trans. on Wireless Communications, vol. 9, no. 12, pp. 3770-3778, Dec. 2010. (SCI, IF 1.903, JCR Top 15.79%)
  31. S.-H. Kong*, “TOA and AOD Statistics for Gaussian Downlink Scatterer Distribution Model,” IEEE Trans. on Wireless Communications, vol.  8, no.  5, pp. 2609-2617, May 2009. (SCI, IF 2.181, JCR Top 21.22%)

Other Publications in respected journals and Magazines

  1.  S.-H. Kong, “Introduction to Autonomous Vehicles and Electronics Laboratory at KAIST”, IEEE ITS Magazine, 2022.
  2.  S.-H. Kong, Juan Carlos Cano, Yisheng Lv, Le Hai Vu, Brendan Morris, Jun-Won Choi, and Dongsuk Kum, “Special Issue Editorial: ITS empowered by AI technologies,”, IEEE Trans. on Intelligent Transportation Systems, 2019.
  3.  S.-H. Kong, Jose A. Lopez-Salcedo, Yuanxin Wu, and Euiho Kim, “Special Section Editorial: GNSS, Localization, and Navigation Technologies,” IEEE Access, 2019

TOP AI conferences

  1.  D.-H. Paek, S.-H. Kong*, and Kevin Tirta Wijaya, “K-Lane: Lidar Lane Dataset and Benchmark for Urban Roads and Highways”, IEEE/CVF Computer Vision and Pattern Recognition (CVPR), Workshop on Autonomous Driving (WAD), June. 2022.

Respected International conferences

  1.  D.-H. Paek, Kevin Tirta Wijaya, and S.-H. Kong*, “Row-wise Lidar Lane Detection Network with Lane Correlation Refinement”, IEEE Intelligent Transportation Systems Conference (ITSC), 2022. 
  2.  K. T. Wijaya, D.-H. Paek, and S.-H. Kong*, “Multiview Attention for 3D Object Detection in Lidar Point Cloud”, IEEE ICAIIC, 2022.
  3. S.-H. Chung, S.-H. Kong*, I Made Aswin Nahredra, S. Cho, “Segmented Encoding for Sim2Real of RL-based End-to-End Autonomous Driving”, IEEE Intelligent Vehicle Symposium (IV2022), June. 2022. 
  4.  S. Cho, B.-S. Kim, T.-S. Kim, and S.-H. Kong*, “Enhancing GNSS Performance and Detection of Road Crossing in Urban Area Using Deep Learning,” IEEE Intelligent Transportation Systems Conference 2019, New Zealand, Oct. 2019.
  5.  N.-H. Lee, S.-H. Chung, and S.-H. Kong*, “Local Path Planner using Lidar and High Definition Map,” 2019 ISGNSS Conference, Oct. 2019.
  6.  S.-H. Chung, S. Cho, T.-S. Kim, N.-H. Lee, and S.-H. Kong*, “GNSS NLOS Discrimination and Multipath Error Compensation using Deep Learning,” 2019 ISGNSS Conference, Oct. 2019.
  7.  M. L. Huang, M.J. Kim, and S.-H. Kong*, “Deep Learning Approach to LPI Radar Recognition,” IEEE Radar Conference 2019, Boston, USA, Apr. 2019.
  8.  C.J. Chae, S.H. Baek, B.Y. Yoon, and S.-H. Kong*, “Deep Q-Learning with LSTM for Traffic Light Control,” APCC 2018, 24th Asia-Pacific Conf. on Commun., Ningbo, China, Nov. 2018.
  9.  H. Ko and S.-H. Kong*, “High-Speed Train Navigation System based on Multi Sensor Fusion Technique with Empirical Data,” ISTS/IWTDCS 2016, Jeju, Rep. of Korea, July 2016
  10.  W. Wang and S.-H. Kong*, “Sub-Nyquist sampling based low complexity fast AltBOC acquisition,” VTC2016, May 2016.
  11.  A. S. Moutchkaev, S.-H. Kong, and A. A., L’vov, “Parameter Estimation of Superimposed Sinusoidals by Data Matrix Subfactorization: Analysis and Results,” 2016 Int’l Conf. on Actual Problems of Electron Devices Engineering (APEDE), 22-23 Sept. 2016, Saratov, Russia
  12.  S.-H. Kong*, S.-Y. Jeon, and W. Wang, “Multipath Resistant Cooperative Positioning Techniques for Vehicular Networks,” IEEE/ION PLANS 2016, Apr. 2016.
  13.  B. Kim and S.-H. Kong*, “Indoor Positioning based on Bayesian Filter using Magnetometer Measurement Difference,” VTC2015, Glasgow, Scotland, May 2015.
  14.  B. Kim and S.-H. Kong*, “Two-Dimensional Compressed Correlator for fast acquisition of CBOC-modulated signal in GNSS,” IEEE/ION PLANS 2014, May 2014.
  15.  K. Yoo and S.-H. Kong*, “PIC Technique with Reduced Complexity in GPS,”
  16.  S. H. Kong* and B. Kim, “FFT-based TDCC for Fast PRN Acquisition in the Presence of Tiered Code,” European Navigation Conference, ENC-GNSS, Apr. 2014.
  17.  B. Kim and S.-H. Kong*, “Determination of Detection Parameters on Fast Acquisition Techniques of GNSS signals,” European Navigation Conference, ENC-GNSS, Apr. 2014.
  18.  B. Kim and S.-H. Kong*, “FFT based Two Dimensional Compressed Correlator for Fast Acquisition in GNSS,” Proc. of ION Pacific PNT, Apr. 2013.
  19.  K. Yoo, H.-S. Kim, and S.-H. Kong*, “Analysis of Anti-jamming Techniques using Filter bank and SVD,” Proc. of ION Pacific PNT, Apr. 2013.
  20.  B. Kim and S.-H. Kong*, “Two Dimensional Compressed Correlator for Fast Acquisition in GNSS,” Proc. of ION ITM, Jan. 2013.
  21.  B. Kim and S.-H. Kong*, “SAR Image Processing Using Super Resolution Spectral Estimation with SVD-Periodogram Method,” Proc. of IEEE/ION PLANS, Apr. 2012.
  22.  S.-H. Kong*, “A Compressed Sensing Technique for GPS Signal Acquisition,” Proc. of ION ITM, Jan. 2012.
  23.  B. Kim and S.-H. Kong*, “SAR Image Processing using Super Resolution Spectral Estimation with Annihilating Filter,” Proc. of APSAR, Sep. 2011.
  24.  W. Nam and S.-H. Kong*, “Modified Least-squares based Iterative Multipath Super-Resolution Algorithm,” Proc. of ION ITM, Jan. 2011.

 

DOMESTIC PUBLICATIONS 

peer reviewed Domestic journals

  1.  Y. Choi, J. Park, and S.-H. Kong*, “Traffic Accident Analysis using Doppler Effect of Engine Sound,” Transactions of KSAE, 2021.
  2.  Y. Choi, J. Park, and S.-H. Kong*, “Speed Analysis based on Engine Sound of Driving Vehicle,” Transactions of KSAE, 2021.
  3.  S. Paek and S.-H. Kong* “강화학습 기반 ATCS 연구 동향”. The Journal of The Korean Institute of Communication Sciences, vol. 35, no. 12, pp. 3-7, Oct.2018.
  4.  M. Kim and S.-H. Kong* 펄스 내 변조 저피탐 레이더 신호 자동 식별”. The Journal of the KIMST, Vol. 21, No. 2, pp. 133-140, 2018.
  5.  B. Kim and S.-H. Kong*, “Ultra-Fast L2-CL Code Acquisition for a Dual Band GPS Receiver,” Journal of Positioning, Navigation, and Timing, vol. 4, no. 4, pp. 151–160, Dec. 2015.
  6.  B. Kim and S.-H. Kong*, “Asynchronous Multilevel Search Strategy for Fast Acquisition of AltBOC Signals,” Journal of Positioning, Navigation, and Timing, vol. 4, no. 4, pp. 161–171, Dec. 2015.
  7.  H. Ko and S.-H. Kong*, “Vehicular Cooperative Navigation Based on H-SPAWN Using GNSS, Vision, and Radar Sensors,” The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 11, pp. 2252–2260, Nov. 2015.
  8.  G.-S. Jeong and S.-H. Kong*, “GIS Based Advanced Positioning Technique for Mobile GPS,” The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 11, pp. 2261–2270, Nov. 2015.
  9.  G.-S. Jeong and S.-H. Kong*, “Pseudo-Correlation-Function Based Unambiguous Tracking Technique for CBOC (6,1,1/11) Signals,” Journal of Positioning, Navigation, and Timing, vol. 4, no. 3, pp. 107–114, Sep. 2015.
  10.  S.-H. Kong*, S.-Y. Jeon and H. Go, “센서융합 측위 기술의 현황과 연구 동향”, Journal of Positioning, Navigation, and Timing, vol. 32, no. 8, pp. 45-53, Sep. 2015.
  11.  S.-H. Kong*, and G.-S. Jeong, “GPS/GNSS Based Vehicular Positioning and Navigation Techniques”, Transactions of the Korean Society of Automotive Engineers, vol. 37, no. 6, pp. 24-28, June. 2015.
  12.  K. Yoo and S.-H. Kong*, “Application and Analysis of 2D FRI (Finite Rate of Innovation) Super-resolution Technique in Vision Navigation,” Transactions of the Korean Society of Automotive Engineers, vol. 23, no. 1, pp. 1–10, Jan. 2015.
  13.  K. Yoo and S.-H. Kong*, “Application and Analysis of 1D FRI (Finite Rate of Innovation) Super-resolution Technique in FMCW Radar,” Transactions of the Korean Society of Automotive Engineers, vol. 22, no. 7, pp. 31–39, Nov. 2014.
  14.  S.-H. Kong*, and K.-Yoo, “GPS Pull-In Search Using Reverse Directional Finite Rate of Innovation (FRI),” Journal of Positioning, Navigation, and Timing, vol. 3, no. 3, pp. 107–116, Sep. 2014.
  15.  B. Kim and S.-H. Kong*, “SAR Image Processing Using SVD-Pseudo Spectrum Technique,” Journal of the Institute of Electronics Engineers of Korea, vol. 50, no. 3, pp. 212–218, Mar. 2013.
  16.  S.-H. Kong*, and S.-J. Han, “센싱 및 계측 기술에서의 혁신: 지구물리 탐사를 위한 압축센싱 및 초고해상도 기술,” 지구물리와물리탐사, vol. 14, no. 4, pp. 335–341, Nov. 2011.

peer reviewed Domestic CONFERENCE

  1.  S.-T. Han, B. Kim, S. Cho, and S.-H. Kong*, “First Arrival Path Detection in Multipath Using CNN,” 2021 IPNT, 2021.
  2.  S.-T. Han, S. Cho, M.-K. Jeong, T. Kim, and S.-H. Kong*, “Imitation Learning-based End-to-end Autonomous Driving with High Definition Map,” 2nd Korea AI Conference, 2021. 
  3.  S.-H. Chung, S. Cho, T.-S. Kim, D.-H. Paek, and S.-H. Kong*, “Reinforcement Learning based End-To-End self-driving Using Variational AutoEncoder” 2020 IPNT conference, Nov. 2020.
  4.  S. Cho, T.-S. Kim, S.-H. Chung, S.-W. Lee, and S.-H. Kong*, “Variable BOC Modulation Technique and Performance Analysis for Next-Generation GNSS” 2020 IPNT conference, Nov. 2020.
  5.  T.-S. Kim, S.-H. Chung, Y.-H. Jang, S.-W. Lee, and S.-H. Kong*, “A study on the message structure of a satellite navigation system that minimizes TTFF(Time To First Fix)” 2020 IPNT conference, Nov. 2020.
  6.  S. Cho, B.-S. Kim, T.-S. Kim, J.-W. Kim, and S.-H. Kong*, “A-GNSS MS-Assisted Mode의 다중위성항법 구현 및 성능 분석” 2018 IPNT conference, Nov. 2018.
  7.  B.-S. Kim, S. Cho, T.-S. Kim, and S.-H. Kong*, “인공지능에 기반한 GNSS 신호의 NLOS 환경 판별 및 측위 알고리즘 성능분석” 2018 IPNT conference, Nov. 2018.
  8.  M.-J. Kim, Y.-B. Sim, and S.-H. Kong*, “정밀 지도와 3차원 점군 지도를 결합한 정밀 자율주행 자동차 항법 시스템” 2018 IPNT conference, Nov. 2018.
  9.  Y.-B. Sim, B.-Y. Woon, and S.-H. Kong*, “도심환경을 위한 MLP 기반 센서 융합 기법” 2018 IPNT conference, Nov. 2017.
  10.  T.-S. Kim, B.-S. Kim, and S.-H. Kong*, “실내 극 미약 GNSS 신호탐색 알고리즘 구현 및 성능분석” 2018 IPNT conference, Nov. 2017.
  11.  T.-S. Kim and S.-H. Kong*, “MS-Assisted GNSS 성능분석” 2016 KGS conference, Nov. 2016.
  12.  S.-I. Han and S.-H. Kong*, “한국고속열차 항법시스템 성능의 실측 분석” 2016 KGS conference, Nov. 2016.
  13.  B.-H. Kim, and S.-H. Kong*, “지자기 센서 오프셋 완화를 위한 측정치 차분 값 기반 실내 측위 기법” 2015 한국통신학회, Jan. 2015.
  14.  S.-Y. Jeon, and S.-H. Kong*, “INS/VLC 융합 시스템 기반 실내 항법 알고리즘 및 성능분석” 2015 한국통신학회, Jan. 2015.
  15.  G.-S. Jeong, M.-W. Jeong, and S.-H. Kong*, “GIS 정보를 이용한 모바일 GPS 위치보정에 관한 연구2018 ITS conference, April. 2015.
  16.  G.-S. Jeong, and S.-H. Kong*, 모바일 GPS 측위능력 향상을 위한 위치추정기법에 관한 연구 한국통신학회, June. 2015.
  17.  H.-W. Ko, and S.-H. Kong*, “GNSS 도심 다중경로오차 완화를 위한 H-SPAWN 알고리즘 향상에 관한 연구2015 한국통신학회, June. 2015.
  18.  G.-S. Jeong, and S.-H. Kong*, “GIS based Virtual Satellite Constrained – Weighted Least Square” 2015 KGS conference, Nov. 2015.
  19.  H.-W. Ko, and S.-H. Kong*, 도심 다중경로 환경에 강인한 GNSS기반 차량 협력 항법시스템2015 KGS conference, Nov. 2015.
  20.  S.-Y. Jeon, and S.-H. Kong*, 협력주행 안정성 향상을 위한 악의적인 차량검출 알고리즘2015 KGS conference, Nov. 2015.
  21.  G.-S. Jeong, and S.-H. Kong*, “의사 상관 함수 기반 합성 이진 옵셋 반송파 신호 추적을 위한 비모호 상관 함수” 2014 KGS conference, Nov. 2018.
  22.  S.-Y. Jeon, and S.-H. Kong*, “Teager-Kaiser 연산자를 이용한 CBOC 신호의 다중경로 지연시간 분석” 2014 KGS conference, Oct. 2014.
  23.  S.-H. Seol, G.-H. Kim, and S.-H. Kong*, “다중센서 기반 고속 열차 항법 시스템의 성능 분석” 2013 KGS conference, Nov. 2013.
  24.  S.-Y. Jeon, S.-H. Seol, G.-H. Kim, and S.-H. Kong*, “INS/GPS 결합 시스템에서의 비선형 필터 성능 비교” 2018 IPNT conference, Nov. 2018.
  25.  J.-S Yoo, K.-W. Yoo, and S.-H. Kong*, “Galileo E1 신호의 Cross Correlation 분석” 2013 KGS conference, Nov. 2013.
  26.  B.-H. Kim, D.-M. Seol, and S.-H. Kong*, “Super-Resolution 기술 기반 최초도달 신호 탐지 기술에서의 단/복수 경로 추정 기법” 2012 KGS conference, Nov. 2012.
  27.  K.-W. Yoo, J.-W. Kim, and S.-H. Kong*, “Comparison and Analysis of Anti-Jamming Technique by using SVD and FFT” 2012 KGS conference, Nov. 2012.
  28.  S.-H. Seol, and S.-H. Kong*, “GNSS 고정밀 신호분해 기술의 성능 비교 분석” 2012 KGS conference, Nov. 2012.
  29.  B.-H. Kim, Artem Muchkaev, and S.-H. Kong*, “수정된 FRI 알고리즘을 이용한 SAR 위성 이미지 프로세싱” 항공우주학회, April. 2011.
  30.  J.-S. Ann, and S.-H. Kong*, “GPS 수신기의 초기 위치획득 시간에 따른 활강 유도무기의 항법 성능 연구” 항공우주학회, April. 2011.
  31.  H.-Y. Han, and S.-H. Kong*, “고정밀 신호 분해 알고리즘을 이용한 다중경로 신호 중 최초도달신호 탐지 성능 연구” 항공우주학회, April. 2012.
  32.  H.-Y. Han, and S.-H. Kong*, “다중경로 채널 환경 모델에 대한 super-resolution 기술의 최초도달신호 탐지 성능 비교 분석” 2011 GNSS Workshop, Nov. 2011.
  33.  H.-Y. Han, and S.-H. Kong*, “ITU-R P.681-7 도시 채널 모델에서 GPS L1 C/A 코드 추적 기술의 성능 비교” 항공우주학회, April. 2010.
  34.  S.-H. Kong*, “Mobile Positioning Technologies for LBS : A-GPS” KRNet, June. 2010.
  35.  N.-Y. Kim, and S.-H. Kong*, “WPAN 기반 ranging system에서의 super resolution 기술비교” 2010 GNSS Workshop, Nov 2010.
  36.  W.-S Nam, and S.-H. Kong*, “비동기 이동통신 망에서 운용되는 A-GNSS를 위한 코드 위상 및 클럭 편자의 동시 가설검정 기법” 2010 GNSS Workshop, Nov 2010.
  37. B.-H. Kim, and S.-H. Kong*, “도심 환경에서의 GPS와 GNSS의 측위 수행 성능 비교” 항공우주학회, April. 2010.
  38. H.-Y. Han, and S.-H. Kong*, “Assisted GNSS 기술의 표준 및 동향 분석” 2010 GNSS Workshop, Nov 2010.
  39. S.-S. Yoo, H.-J.Bang, and S.-H. Kong*, “Wibro 기반 무선 측위 가능성 분석Telecommunications Review, April. 2008.

Awards

  • Outstanding Paper Award, 2nd Korea Artificial Intelligence Conference, 2021
  • 대통령상(1위), 2018 국제대학생자율주행경진대회, 2018
  • IEEE Senior Membership, 2016-present
  • 2015 KAIST Technology Innovation Award, 2015
  • Outstanding Paper Award (H.-W. Ko and S.-H. Kong) – KGS Conference, 2015
  • Outstanding Paper Award (K. Jung and S.-H. Kong) – KGS Conference, 2014
  • Distinguished Contribution Award – LBS Forum, 2004
  • Outstanding Patent Prize, Samsung Electronics Co. Ltd., 1999

Research

General Research Interests      

1. Deep Learning for Autonomous Vehicles 

  • Imitation and Reinforcement Learning for Mobile Robots
  • Deep Learning-based Perception (for Lidar, 4D Radar, and Camera)
  • Reliable AI for Robust Autonomous Driving

2. Vehicle Localization and Navigation

  • Sensor Fusion AI for Precise Localization
  • Cooperative Vehicle Navigation for Urban Environments
  • Assisted-GNSS for Mobile and V2X Communication Systems

Current Research Projects      

1. Meta-Reinforcement Learning-based End-To-End Self-Driving with Rapid Adaptation to Unexpected Novel Situation  (2021-2025)

A self-driving car may run into a trouble when there occurs an UNS (unexpected novel situation) that includes a wheel slip due to partially ice roads, control problems due to the unexpected dynamics change such as flat tire and partial brake misfunction. The project is to develop an innovative AI for self-driving cars that quickly figure out the situation and adapts control appropriately in seconds, which is necessary for driving safety. 

2. Deep Learning for Perception with 4D Radar (2021-2022)

4D (xyz and Doppler) Radar is a new Radar developed for autonmotives in 2020. We are developing perception (deep learning) for 4D Radar for the first time in the world. And we already made world first progress such as developing and distributing 4D Radar dataset and publishing the first study on 4D Radar deep learning algorithms. 

3. Development of AI technology that continuously improves itself as the situation changes in the real world (2020-2023)

We are participating this group project, where we are developing AI for self-driving cars that improves its driving policy quickly when the cars meet real environments that are different from its prior experience. 

 

Distinguished R&D Achievements           

1. Self-Driving Car Competition (2018) in Korea   2018

My research team won the President Prize (of Korea) in the biennial 2018 International Student Self-Driving Car Competition, which is sponsored by the Korean government and Hyundai Motors Group. There are many technologies that we have developed for the self-driving car; two of the pioneering technologies are the Lidar sensing system and path planning algorithm. 

2. Deep Learning-based LPI Radar Recognition Technique  2016-2018

Low probability of intercept (LPI) radar is one of the state-of-the-art military radars in the electronic warfare, where the continuous waveform is specially modulated and transmitted with low power so that the opponents cannot easily detect the presence of the signal. LPI radar detection is a hot-topic in radar research these days, but my research on this topic has produced by far the best performing techniques for LPI radar detection, classification, and feature extraction using state-of-the-art deep neural networks. Because of that, I was invited to deliver a talk at the LPI radar special section of the IEEE radar conference-2019.

3. Mobile Positioning System for Korean LTE Carriers 2015-2018

LTE carriers are providing mobile positioning service using Assisted-GNSS, Wifi, and cellular localization. I have been the technology leader in the development of Assisted-GNSS robust to urban environments and the localization system using cellular signals for the two major Korean LTE carriers, SKT and KT. The system for SKT has started its service around Seoul, Korea, and the system for KT will be on service in 2020. 

4. High-Sensitivity and Fast Acquisition for Severely Attenuated GNSS Signals  2013-2017

This research is to develop super-sensitivity and ultra-fast GNSS signal detection technique to quickly define user location with weak GNSS signals in the indoor environments. I have developed a breakthrough GPS signal acquisition technique (Synthesized Doppler-frequency Hypothesis Testing: SDHT) that requires tens of thousand times less computational cost and, thus, takes tens of thousands less time to perform a very long coherent correlation necessary for indoor GNSS positioning. SDHT is introduced in IEEE JSAC in 2015 and IEEE Signal Processing Magazine in 2017.

5. Multisensor Fusion based Precise Navigation Syst. for Korean Express Trains (KTX)  2013-2016

Developing an accurate and seamless navigation system for express trains running faster than 300Km per hour is a big challenge. My team had successfully developed a federated Kalman filter based navigation system to combine various sensors such as DGPS, INS, RFID, and wheel-encoder, which produces precise positioning estimate (less than 2m instantaneous error at 300Km/hr speed) at any time any environments including tunnels. The performance of the developed system was demonstrated through field tests on mountainous train tracks, where we had tunnels of several kilometers long. 

6. Multipath Error Modeling and Mitigation Techniques for LTE and GNSS  2010-2014

Due to the nonlinear distortion by the receiver signal processing chain, noise, and interference between multipath, the resolved-and-detected first arrival path (RFAP) is very often different from the true first arrival path in the channel. Also, the spatiotemporal distribution of multipath in the given environments is hard to predict, and there hasn’t been a reliable multipath mitigation technology. These problems have been unexplained, but I have done pioneering research on these topics to explain the spatiotemporal distribution of urban multipath for GNSS and LTE and the nonlinear distortion making RFAP different from the first arrival path. I also developed so-far the best RFAP detection techniques using least-square and deep learning. 

7. Repeater Signal Identification System for Positioning in Underground Areas 2002-2004

In practice, the presence of repeaters or remote radio head ruins mobile positioning systems using temporal delay or angular measurements of the signals, because their signals are the same signals transmitted at the base station. In 2003, I invented and developed the world’s first (and best so far) repeater positioning technology that enabled the largest Korean CDMA carrier, SKT, to expand their location-based services (LBS) to the underground stations and malls for the first time in the world. I sold the entire license, and later the technology made SKT become the national location tracking service provider of electronic wedges.

Teaching

GRADUATE COURSES (IN ENGLISH, KAIST)

  • GT508 Sensing and Navigation Systems(2012-present)
  • GT560 Principles and Applications of the Kalman Filter(2015-present)
  • PD803 – Understanding and Design of AI for Self-Driving Cars(2019-prenset)
  • GT869- Deep Learning for Autonomous Vehicle Sensors(2017, 2020)
  • GT869 – Wireless Positioning and Localization Systems(2014)
  • GT869 – Autonomous Navigation and Self-Driving Systems(2012, 2018)

UNDERGRADUATE COURSES (IN ENGLISH, KAIST)

  • MAE300 Principles of Signal Processing for Aerospace Engineering(2010-2011)
  • MAE307 Applied Electronics(2010-2011)

Students

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