Relationships between GPS-signal propagation errors and EISCAT observations

• Published in: Annales Geophysicae
• Main Authors: Jakowski, N., Sardon, E., Engler, E., Jungstand, A., Klähn, D.
• Format: Text
• Language: English
• Published: 2018
• Subjects: EISCAT
• Online Access: https://doi.org/10.1007/s00585-996-1429-0; https://angeo.copernicus.org/articles/14/1429/1996/

When travelling through the ionosphere the signals of space-based radio navigation systems such as the Global Positioning System (GPS) are subject to modifications in amplitude, phase and polarization. In particular, phase changes due to refraction lead to propagation errors of up to 50 m for single-frequency GPS users. If both the L1 and the L2 frequencies transmitted by the GPS satellites are measured, first-order range error contributions of the ionosphere can be determined and removed by difference methods. The ionospheric contribution is proportional to the total electron content (TEC) along the ray path between satellite and receiver. Using about ten European GPS receiving stations of the International GPS Service for Geodynamics (IGS), the TEC over Europe is estimated within the geographic ranges -20°≤ λ ≤40°E and 32.5°≤ Φ ≤70°N in longitude and latitude, respectively. The derived TEC maps over Europe contribute to the study of horizontal coupling and transport proces- ses during significant ionospheric events. Due to their comprehensive information about the high-latitude ionosphere, EISCAT observations may help to study the influence of ionospheric phenomena upon propagation errors in GPS navigation systems. Since there are still some accuracy limiting problems to be solved in TEC determination using GPS, data comparison of TEC with vertical electron density profiles derived from EISCAT observations is valuable to enhance the accuracy of propagation-error estimations. This is evident both for absolute TEC calibration as well as for the conversion of ray-path-related observations to vertical TEC. The combination of EISCAT data and GPS-derived TEC data enables a better understanding of large-scale ionospheric processes.