Estimating satellite and receiver differential code bias using a relative Global Positioning System network

摘要

Precise total electron content (TEC) is required to produce accuratespatial and temporal resolution of global ionosphere maps (GIMs). Receiversand satellite differential code biases (DCBs) are one of the main errorsources in estimating precise TEC from Global Positioning System (GPS)data. Recently, researchers have been interested in developing models andalgorithms to compute DCBs of receivers and satellites close to thosecomputed from the Ionosphere Associated Analysis Centers (IAACs). Here weintroduce a MATLAB code called Multi Station DCB Estimation (MSDCBE) tocalculate satellite and receiver DCBs from GPS data. MSDCBE based ona spherical harmonic function and a geometry-free combination of GPS carrier-phase, pseudo-range code observations, and weighted least squares wasapplied to solve observation equations and to improve estimation of DCBvalues. There are many factors affecting the estimated values of DCBs. The firstone is the observation weighting function which depends on the satelliteelevation angle. The second factor is concerned with estimating DCBs usinga single GPS station using the Zero Difference DCB Estimation (ZDDCBE) code orusing the GPS network used by the MSDCBE code. The third factor is the number of GPSreceivers in the network. Results from MSDCBE were evaluated and comparedwith data from IAACs and other codes like M_DCB and ZDDCBE.The results of weighted (MSDCBE) least squares show an improvement forestimated DCBs, where mean differences from the Center for Orbit Determinationin Europe (CODE) (University of Bern, Switzerland) are less than 0.746 ns. DCBsestimated from the GPS network show better agreement with IAAC than DCBsestimated from precise point positioning (PPP), where the mean differences are less than 0.1477 and1.1866 ns, respectively. The mean differences of computed DCBs improved byincreasing the number of GPS stations in the network.