Simulating the Availability of Integrated GNSS Positioning in Dense Urban Areas

통합 GNSS 환경에서 도시공간 위성측위의 가용성 평가 시뮬레이션

  • 서용철 (부경대학교 위성정보과학과) ;
  • 이양원 (동경대학 공간정보과학연구센터)
  • Published : 2007.06.30

Abstract

This paper describes the availability of the forthcoming integrated GNSS(Global Navigation Positioning System) positioning that includes GPS(Global Positioning System), Galileo, and QZSS(Quasi-Zenith Satellites System). We built a signal propagation model that identifies direct, multipath, and diffraction signals, using the principles of specular reflection and ray tracing technique. The signal propagation model was combined with 3D GIS(three-dimensional geographic information system) in order to measure the satellite visibility and positioning error factors, such as the number of visible satellites, average elevation of visible satellites, optimized DOP(dilution of position) values, and the portion of multipath-producing satellites. Since Galileo and QZSS will not be fully operational until 2010, we used a simulation in comparing GPS and GNSS positioning for a $1km{\times}1km$ developed area in Shinjuku, Tokyo. To account for local terrain variation. we divided the target area into 40,000 $5m{\times}5m$ grid cells. The number of visible satellites and that of multipath-free satellites will be greatly increased in the integrated GNSS environment while the average elevation of visible satellites will be higher in the GPS positioning. Much decreased PDOP(position dilution of precision) values indicate the appropriate satellite/user geometry of the integrated GNSS; however, in dense urban areas, multipath mitigation will be more important than the satellite/user geometry. Thus, the efforts for applying current technologies of multipath mitigation to the future GNSS environment will be necessary.

본 연구에서는 가까운 장래에 실현될 GNSS(Global Navigation Positioning System) 결합측위의 가용성을 평가하기 위하여, GPS(Global Positioning System), Galileo 및 QZSS(Quasi-Zenith Satellites System)의 직달파(direct signal), 반사파(reflected signal), 회절파(diffracted signal) 식별을 위한 신호 전달 모형을 수립하고 이를 3차원 지리정보시스템과 결합함으로써, 위성 가시도와 측위 오차 요소를 모사 측정하였다. 중고층 빌딩이 밀집한 일본 동경도청 부근의 $1km{\times}1km$ 구역을 40,000개의 $5m{\times}5m$ 격자로 구획하여 실시한 시뮬레이션을 통해, GPS 측위와 GNSS 결합측위에 있어서 가시위성의 개수, 위성 고도, 정밀도 저하율(dilution of position : DOP), 의사거리 다중 경로 오차(pseudorange multipath error : PME)를 비교 평가하였다. GNSS 결합측위에서는 가시위성 및 직달파 위성의 개수가 현격히 증가함을 확인할 수 있었으며, 위성고도의 평균은 GPS 측위에서보다 약간 낮게 나타나지만, 위성들의 기하학적 배치가 양호하게 이루어져 정밀도 저하율이 매우 감소함을 알 수 있다. 고밀도 도시공간에서는 빌딩 등의 전파 반사로 인해 발생하는 의사거리 다중경로 오차를 완화하는 것이 사용자 위치 정확도를 향상시키기 위한 핵심적인 요소이므로, 수신기 안테나의 설계 및 배치, 신호처리 및 공간통계 기법 등을 GNSS 결합측위에 적합하도록 개선하는 것이 필요할 것이다.

Keywords

References

  1. 배경호, 허민, 이용욱, 이재원 (2006), 유럽의 Galileo 시스템을 이용한 GNSS 측위 성능 향상, 한국측량학회 2006 춘계학술발표회 논문집, pp. 33-37
  2. 이동락, 이흥규, 배경호 (2005), GPS/Galileo 결합 시스템의 측위 성능 분석, 한국측량학회지, 제 23권, 제 3호, pp. 283-292
  3. Conley, R., Cosentino, R., Hegarty, C.J., Kaplan, E.D., Leva, J.L., de Haag, M.U. and van Dyke, K. (2006), Performance of stand-alone GPS, In: Kaplan, E.D. and Hegarty, C.J. (ed.), Understanding GPS: Principle and Applications, Artech House, Boston London, pp. 301-378
  4. Dellago, R., Detoma, E. and Luongo, F. (2003), Galileo-GPS interoperability and compatibility: a synergetic viewpoint, Proceedings of Institute of Navigation - Global Positioning System/Global Navigation Satellite System 2003, Portland, Oregon, pp. 542-548
  5. Kawano, I., Mokuno, M., Kogure, S. and Kishimoto, M. (2004), Japanese experimental GPS augmentation using Quasi-Zenith Satellite System (QZSS), Proceedings of Institute of Navigation - Global Navigation Satellite System 2004, Long Beach, California, pp. 175-181
  6. Li, J., Taylor, G., Kidner, D. and Ware M. (2004), Prediction of GPS multipath effect using LiDAR digital surface models and building footprints, Lecture Notes in Computer Science, Vol. 4295, pp. 42-53
  7. Lee, Y-W., Sub, Y.-C. and Shibasaki, R. (2006), Simulation-based estimation of multipath mitigation using 3D-GIS and spatial statistics, Proceedings of Institute of Navigation - Global Navigation Satellite System 2006, pp. 1778-1783
  8. Park, C.-W. and How, J.P. (2001), Quasi-optimal satellite selection algorithm for real-time applications, Proceedings of Institute of Navigation - Global Positioning System 2001, pp. 3018-3028
  9. Seeber, G. (2003), Satellite Geodesy: Foundations, Methods, and Applications. Walter de Gruyter, Berlin
  10. Suh, Y.-C., Konishi, Y., Hakamata, T., Manandhar, D., Shibasaki, R. and Kubo, N. (2004), Evaluation of multipath error and signal propagation in complex 3D urban environments for GPS multipath identification, Proceedings of Institute of Navigation - Global Navigation Satellite System 2004, Long Beach, California, pp. 1147-1156
  11. Suh, Y.-C. and Shibasaki, R. (2007), Evaluation of satellite-based navigation services in complex urban environments using a three-dimensional GIS, IEICE Transactions on Communications, IN PRESS
  12. Taylor, G., Li, J., Kidner, D. and Ware, M. (2005), Surface modelling for GPS satellite visibility, Lecture Notes in Computer Science, Vol. 3833, pp. 281-295
  13. Taylor, G., Li, J., Kidner, D., Brunsdon, C. and Ware, M. (2007), Modelling and prediction of GPS availability with digital photogrammetry and LiDAR, International Journal of Geographical Information Science, Vol. 21, No. 1, pp. 1-20 https://doi.org/10.1080/13658810600816540
  14. Ward, P.W., Betz, J.W. and Hegarty, C.J. (2006), Satellite signal acquisition, tracking, and data modulation, In: Kaplan, E.D. and Hegarty, C.J. (ed.), Understanding GPS: Principle and Applications, Artech House, Boston London, pp. 153-241