- Volume 7 Issue 3
DOI QR Code
Database based Global Positioning System Correction
데이터베이스 기반 GPS 위치 보정 시스템
- Moon, Jun-Ho (Electrical & Electronic Engineering, Yonsei University) ;
- Choi, Hyuk-Doo (Electrical & Electronic Engineering, Yonsei University) ;
- Park, Nam-Hun (Computer Science, Anyang University) ;
- Kim, Chong-Hui (Agency for Defense Development (ADD)) ;
- Park, Yong-Woon (Agency for Defense Development (ADD)) ;
- Kim, Eun-Tai (Electrical & Electronic Engineering, Yonsei University)
- Received : 2012.05.24
- Accepted : 2012.08.10
- Published : 2012.08.31
A GPS sensor is widely used in many areas such as navigation, or air traffic control. Particularly, the car navigation system is equipped with GPS sensor for locational information. However, when a car goes through a tunnel, forest, or built-up area, GPS receiver cannot get the enough number of satellite signals. In these situations, a GPS receiver does not reliably work. A GPS error can be formulated by sum of bias error and sensor noise. The bias error is generated by the geometric arrangement of satellites and sensor noise error is generated by the corrupted signal noise of receiver. To enhance GPS sensor accuracy, these two kinds of errors have to be removed. In this research, we make the road database which includes Road Database File (RDF). RDF includes road information such as road connection, road condition, coordinates of roads, lanes, and stop lines. Among the information, we use the stop line coordinates as a feature point to correct the GPS bias error. If the relative distance and angle of a stop line from a car are detected and the detected stop line can be associated with one of the stop lines in the database, we can measure the bias error and correct the car's location. To remove the other GPS error, sensor noise, the Kalman filter algorithm is used. Additionally, using the RDF, we can get the information of the road where the car belongs. It can be used to help the GPS correction algorithm or to give useful information to users.
Supported by : Agency for Defense Development (ADD)
- R. L. Greenspan, "GPS and inertial integration", Global Positioning System: Theory and Applications, vol. 164, pp.187-218, 1996.
- D. A. Grejner-Brzezinska, R. Da, and C. Toth, "GPS error modeling and OTF ambiguity resolution for high-accuracy GPS/INS integrated system", Journal of Geodesy, vol. 72, no.11, pp.628-638, Nov, 1998.
- J. Wendel, O. Meister, C. Schlaile, and G. F. Trommer, "An integrated GPS/MEMS-IMU navigation system for an autonomous helicopter", Aerospace Science and Technology, vol. 10, pp.527-533, Sep, 2006. https://doi.org/10.1016/j.ast.2006.04.002
- Patrick J. F. Carle, Paul T. Furgale, Timothy D. Barfoot, "Long-range rover localization by matching LIDAR scans to orbital elevation maps", Journal of Field Robotics, vol. 27, pp.344-370, June, 2011.
- F. Viani, P. Rocca, G. Oliveri, D. Trinchero, A. Massa, "Localization, tracking, and imaging of targets in wireless sensor networks : An invited review", Radio Science, vol. 46, 2011.
- S. Cho, J. Lee, "Localization of a high-speed mobile robot using global features", Robotica, vol. 29, pp.757-765, September, 2011. https://doi.org/10.1017/S0263574710000536
- H, Bian, Z, Jin, W, Tian "IAE-adaptive Kalman filter for INS/GPS integrated navigation system", BIAI Journals & Magazines, vol. 17, pp.502-508, 2006.
- J. Moon, H. Choi, N. H. Park, Y. W. Park, C. H. Kim, and E. Kim, "LiDAR sensor matching system using database", International Conference on Automation and Control Engineering, pp.995-998, January, 2012.
- 김상섭, 진용, 조성윤, 박찬국, 지규인, 이영재, "저급 IMU의 오차 보정", 항공우주학회 춘계학술발표회 논문집, pp.197-200, 2000.
- 김종원, 이택진, 소형민, 전상훈, 김강호, 기창돈, "멀티 안테나와 반송파위상 측정치를 이용한 의사 위성 위치 측정 방법", 한국항공우주학회 춘계학술대회, pp.614-620, 2011.
- 차득기 저, "GPS 측량이해", 성림출판사, May, 2006.
- 노성우, 김태균, 고낙용, 배영철, "이동로봇의 GPS 위치 정보 보정을 위한 파티클 필터 방법" 한국전자통신학회 논문지 7권 2호, pp.381-389, 2012.