DOI QR코드

DOI QR Code

국내 GNSS 오차 성분별 공간 상관성 및 선형 모델링 특성 분석

Analysis of Spatial Correlation and Linear Modeling of GNSS Error Components in South Korea

  • 김성익 ;
  • 이예빈 ;
  • 조용래 ;
  • 차윤호 ;
  • 박병운 ;
  • 박슬기 ;
  • 박상현
  • Sungik Kim (Department of Aerospace Engineering and Department of Convergence Engineering for Intelligent Drone, Sejong University) ;
  • Yebin Lee (Department of Aerospace Engineering and Department of Convergence Engineering for Intelligent Drone, Sejong University) ;
  • Yongrae Jo (Department of Aerospace Engineering and Department of Convergence Engineering for Intelligent Drone, Sejong University) ;
  • Yunho Cha (Department of Aerospace Engineering and Department of Convergence Engineering for Intelligent Drone, Sejong University) ;
  • Byungwoon Park (Department of Aerospace Engineering and Department of Convergence Engineering for Intelligent Drone, Sejong University) ;
  • Sul Gee Park (Maritime PNT Research Office) ;
  • Sang Hyun Park (Maritime PNT Research Office)
  • 투고 : 2024.05.16
  • 심사 : 2024.06.17
  • 발행 : 2024.09.15

초록

Errors included in Global Navigation Satellite System (GNSS) measurements degrade the performance of user position estimation but can be mitigated by spatial correlation properties. Augmentation systems providing correction data can be broadly categorized into State Space Representation (SSR) and Observation Space Representation (OSR) methods. The satellite-based cm-level augmentation service based on the SSR broadcasts correction data via satellite signals, unlike the traditional Real-Time Kinematic (RTK) and Network RTK methods, which use OSR. To provide a large amount of correction data via the limited bandwidth of the satellite communication, efficient message structure design considering service area, correction generation, and broadcast intervals is necessary. For systematic message design, it is necessary to analyze the influence of error components included in GNSS measurements. In this study, errors in satellite orbits, satellite clocks for GPS, Galileo, BeiDou, and QZSS satellite constellations ionospheric and tropospheric delays over one year were analyzed, and their spatial decorrelations and linear modeling characteristics were examined.

키워드

과제정보

This research was supported by a grant from National R&D Project "Development of ground-based centimeter-level maritime precise PNT technologies" funded by the Ministry of Oceans and Fisheries (RS-2020-KS201371).

참고문헌

  1. Bang, E. & Lee, J. 2013, Methodology of automated ionosphere front velocity estimation for ground-based augmentation of GNSS, Radio Science, 48, 659-670. https://doi.org/10.1002/rds.20066
  2. Kim, D., Park, B., Lee, S., Cho, A., & Kim, J., et al. 2008, Design of efficient navigation message format for UAV pseudolite navigation system, IEEE Transactions on Aerospace and Electronic Systems, 44, 1342-1355. https://doi.org/10.1109/TAES.2008.4667713
  3. Kim, J., Song, J., No, H., Han, D., Kim, D., et al. 2017, Accuracy improvement of DGPS for low-cost single-frequency receiver using modified Flachen Korrektur parameter correction, ISPRS International Journal of GeoInformation, 6, 222. https://doi.org/10.3390/ijgi6070222
  4. Kim, M. & Kim, J. 2014, An analysis on the long-term variation of the GPS broadcast ephemeris errors, Journal of Advanced Navigation Technology, 18, 421-428. https://doi.org/10.12673/jant.2014.18.5.421
  5. Klobuchar, J. A. 1987, Ionospheric time-delay algorithm for single-frequency GPS users, IEEE Transactions on Aerospace and Electronic Systems, AES-3, 325-331. https://doi.org/10.1109/TAES.1987.310829
  6. Landskron, D. & Bohm, J. 2018, VMF3/GPT3: refined discrete and empirical troposphere mapping functions, Journal of Geodesy, 92, 349-360. https://doi.org/10.1007/s00190-017-1066-2
  7. Lee, D.-K., Lee, Y., & Park, B. 2023, Carrier Phase Residual Modeling and Fault Monitoring Using Short-Baseli-ne Double Difference and Machine Learning, Mathematics, 11, 2696. https://doi.org/10.3390/math11122696
  8. Lim, C., Park, B., & Yun, Y. 2023, L1 SFMC SBAS Message for Service Expansion of Multi-Constellation GNSS Support, IEEE Access, 11, 81690-81710. https://doi.org/10.1109/ACCESS.2023.3300580
  9. Montenbruck, O., Schmid, R., Mercier, F., Steigenberger, P., Noll, C., et al. 2015, GNSS satellite geometry and attitude models, Advances in Space Research, 56, 1015-1029. https://doi.org/10.1016/j.asr.2015.06.019
  10. Montenbruck, O., Steigenberger, P., & Hauschild, A. 2018, Multi-GNSS signal-in-space range error assessment-Methodology and results, Advances in Space Research, 61, 3020-3038. https://doi.org/10.1016/j.asr.2018.03.041
  11. Park, B, Lee, J, Kim Y, Yun, H., & Kee, C. 2013, DGPS Enhancement to GPS NMEA Output Data: DGPS by Correction Projection to Position-Domain, Journal of Navigation, 66, 249-264. https://doi.org/10.1017/S0373463312000471
  12. Park, B. & Kee, C. 2010, The compact network RTK method: An effective solution to reduce GNSS temporal and spatial decorrelation error, The Journal of Navigation, 63, 343-362. https://doi.org/10.1017/S0373463309990440
  13. Park, B., Kim, J., Kee, C., Cleveland, A., Parsons, M., et al. 2006, RRC unnecessary for DGPS messages, IEEE transactions on aerospace and electronic systems, 42, 1149-1160. https://doi.org/10.1109/TAES.2006.248220
  14. Park, B., Lim, C., Wang, J., & Morton, Y. T. J. 2022, Horizontal drift velocity and dimensions of ionospheric irregularities using ROT from a GNSS receiver array, IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14. https://doi.org/10.1109/TGRS.2022.3186839
  15. Park, K. & Seo, J. 2021, Single-antenna-based GPS antijamming method exploiting polarization diversity, IEEE Transactions on Aerospace and Electronic Systems, 57, 919-934. https://doi.org/10.1109/TAES.2020.3034025
  16. Schaer, S., Gurtner, W., & Feltens, J. 1998, IONEX: The ionosphere map exchange format version 1, In Proceedings of the IGS AC workshop, Darmstadt, Germany, 9-11 February 1998.
  17. Son, P.-W., Rhee, J. H., Hwang, J., & Seo, J. 2019, Universal kriging for Loran ASF map generation, IEEE Transactions on Aerospace and Electronic Systems, 55, 1828-1842. https://doi.org/10.1109/TAES.2018.2876587
  18. Song, J., Park, B., & Kee, C. 2016, Comparative Analysis of Height-Related Multiple Correction Interpolation Methods with Constraints for Network RTK in Mountainous Areas, Journal of Navigation, 69, 991-1010. https://doi.org/10.1017/S0373463316000011
  19. Steigenberger, P. & Montenbruck, O. 2022, IGS Satellite Metadata File Description, Version 1.00. https://doi.org/10.57677/metadata-sinex
  20. Strasser, S., Banville, S., Kvas, A., Loyer, S., & Mayer-Gurr, T. 2021, Comparison and generalization of GNSS satellite attitude models, EGU General Assembly 2021, online, 19-30 Apr 2021, EGU21-7825. https://doi.org/10.5194/egusphere-egu21-7825
  21. Wang, S., Zhai, Y., & Zhan, X. 2021, Characterizing BDS signal-in-space performance from integrity perspective, Navigation, 68, 157-183. https://doi.org/10.1002/navi.409
  22. Yoon, D., Kee, C., Seo, J., & Park, B. 2016, Position Accuracy Improvement by Implementing the DGNSS-CP Algorithm in Smartphones, Sensors, 16, 910. https://doi.org/10.3390/s16060910
  23. Yoon, H., Seok, H., Lim, C., & Park, B. 2020, An Online SBAS Service to Improve Drone Navigation Performance in High-Elevation Masked Areas, Sensors, 20, 3047. https://doi.org/10.3390/s20113047
  24. Yun, J. & Park, B. 2024, A GNSS/Barometric Altimeter Tightly coupled Integration for Three-Dimensional Semi-indoor Mapping with Android Smartphones, IEEE Geoscience and Remote Sensing Letters, 21, 8001005. https://doi.org/10.1109/LGRS.2024.3365610