Iranian Permanent GPS Network Receivers Differential Code Biases Estimation Using Global Ionospheric Maps

Measurements of the dual frequency Global Positioning System (GPS) receivers can be used to calculate the electron density and the total electron content (TEC) of the ionosphere layer of the Earth atmosphere. TEC is a key parameter for investigating the ongoing spatial and temporal physical process of the ionosphere. For accurate estimation of TEC from GPS measurements, GPS satellites and GPS receivers’ instrumental frequency-dependent biases should be removed from the measurements properly. Instrumental biases are thought to be due to the delays caused by the analog hardware of the satellite and receiver.  Thus Differential Code Bias (DCB) of GPS satellites and receivers are one of the most important error sources and in fact, the unknowns in the TEC calculation and consequently the positioning using GPS code observations. International GNSS Services (IGS) estimates and publishes the DCBs of GPS satellites and its network GPS receivers as an ionosphere single layer model byproduct. Although DCBs of all GPS satellites are provided by IGS, but DCBs of GPS receivers are not provided for all IGS network GPS receivers every days, Furthermore the DCBs of regional and local GPS networks receivers are not provided by IGS. Estimating the DCBs of GPS receivers in regional and local networks independent of single-layer ionosphere modeling will be practical. Therefore the aim this paper is to use Global Ionospheric Maps (GIM) and GPS satellite DCBs which are published by IGS to estimate Iranian Permanent GPS Network (IPGN) receivers DCBs independent of single-layer ionosphere modeling. Code geometry-free linear combination of GPS observations, also known as the ionospheric observable are used in receivers DCBs estimating. Code geometry-free observations are absolute value but they are noisier than more precise but relative carrier phase observations. In most researches the “carrier to code leveling process” algorithm is used to smooth code geometry-free observations which benefit from both ambiguity independent code observations as well as the high precision of carrier phase observations. But in this paper the moving average filter, which is a kind of low pass filters was used for smoothing and reducing the noise of code geometry-free observations. The algorithm of this method is easier and has less computational load with the same accuracy in smoothing result. Spatial and temporal interpolations are used to derive the VTEC values form IGS GIM at each epoch. The interpolated VTEC is mapped into STEC using a mapping function and having GPS satellite DCBs from IGS, the GPS receivers DCBs will be computed at each epoch. Daily averages of derived GPS receivers DCBs are computed to compare it with the IGS published one. First, the proposed method was implemented on some IGS network stations in different latitudes and in two days with quiet and disturbed solar activity and the values derived for receivers DCB were compared with the values published by Center for Orbit Determination in Europe (CODE) as a member of IGS ionosphere working group. The maximum difference between estimated DCB and DCB from CODE is 0.644 ns and the root mean square of these differences (RMSE) is equal to 0.257 ns which show the high efficiency of the proposed method for GPS receivers DCBs estimation. Then IPGN GPS receivers DCBs are computed using proposed method.