(2018) Estimation and analysis of multi-GNSS differential code biases using a hardware signal simulator. GPS Solutions, 22 . 32/1-32/12. ISSN 1521-1886 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/49019/9/s10291-018-0700-7.pdf
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AbstractIn ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a 'known' parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The 'known' receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1-2 ns was found between the estimated DCBs and the manufacturer's measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.