Estimating satellite and receiver differential code bias using a relative Global Positioning System network
<p>Precise total electron content (TEC) is required to produce accurate spatial and temporal resolution of global ionosphere maps (GIMs). Receivers and satellite differential code biases (DCBs) are one of the main error sources in estimating precise TEC from Global Positioning System (GPS) dat...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-11-01
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| Series: | Annales Geophysicae |
| Online Access: | https://www.ann-geophys.net/37/1039/2019/angeo-37-1039-2019.pdf |
| _version_ | 1818136137338716160 |
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| author | A. A. Elghazouly M. I. Doma A. A. Sedeek |
| author_facet | A. A. Elghazouly M. I. Doma A. A. Sedeek |
| author_sort | A. A. Elghazouly |
| collection | DOAJ |
| description | <p>Precise total electron content (TEC) is required to produce accurate
spatial and temporal resolution of global ionosphere maps (GIMs). Receivers
and satellite differential code biases (DCBs) are one of the main error
sources in estimating precise TEC from Global Positioning System (GPS)
data. Recently, researchers have been interested in developing models and
algorithms to compute DCBs of receivers and satellites close to those
computed from the Ionosphere Associated Analysis Centers (IAACs). Here we
introduce a MATLAB code called Multi Station DCB Estimation (MSDCBE) to
calculate satellite and receiver DCBs from GPS data. MSDCBE based on
a spherical harmonic function and a geometry-free combination of GPS carrier-phase, pseudo-range code observations, and weighted least squares was
applied to solve observation equations and to improve estimation of DCB
values. There are many factors affecting the estimated values of DCBs. The first
one is the observation weighting function which depends on the satellite
elevation angle. The second factor is concerned with estimating DCBs using
a single GPS station using the Zero Difference DCB Estimation (ZDDCBE) code or
using the GPS network used by the MSDCBE code. The third factor is the number of GPS
receivers in the network. Results from MSDCBE were evaluated and compared
with data from IAACs and other codes like M_DCB and ZDDCBE.
The results of weighted (MSDCBE) least squares show an improvement for
estimated DCBs, where mean differences from the Center for Orbit Determination
in Europe (CODE) (University of Bern, Switzerland) are less than 0.746 ns. DCBs
estimated from the GPS network show better agreement with IAAC than DCBs
estimated from precise point positioning (PPP), where the mean differences are less than 0.1477 and
1.1866 ns, respectively. The mean differences of computed DCBs improved by
increasing the number of GPS stations in the network.</p> |
| first_indexed | 2024-12-11T09:35:37Z |
| format | Article |
| id | doaj.art-be737ef296964f859998345e1533f5a4 |
| institution | Directory Open Access Journal |
| issn | 0992-7689 1432-0576 |
| language | English |
| last_indexed | 2024-12-11T09:35:37Z |
| publishDate | 2019-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Annales Geophysicae |
| spelling | doaj.art-be737ef296964f859998345e1533f5a42022-12-22T01:12:52ZengCopernicus PublicationsAnnales Geophysicae0992-76891432-05762019-11-01371039104710.5194/angeo-37-1039-2019Estimating satellite and receiver differential code bias using a relative Global Positioning System networkA. A. Elghazouly0M. I. Doma1A. A. Sedeek2Faculty of Engineering, Menoufia University, Menoufia, EgyptFaculty of Engineering, Menoufia University, Menoufia, EgyptCivil Department, El Behira Higher Institute of Engineering and Technology, El Behira, Egypt<p>Precise total electron content (TEC) is required to produce accurate spatial and temporal resolution of global ionosphere maps (GIMs). Receivers and satellite differential code biases (DCBs) are one of the main error sources in estimating precise TEC from Global Positioning System (GPS) data. Recently, researchers have been interested in developing models and algorithms to compute DCBs of receivers and satellites close to those computed from the Ionosphere Associated Analysis Centers (IAACs). Here we introduce a MATLAB code called Multi Station DCB Estimation (MSDCBE) to calculate satellite and receiver DCBs from GPS data. MSDCBE based on a spherical harmonic function and a geometry-free combination of GPS carrier-phase, pseudo-range code observations, and weighted least squares was applied to solve observation equations and to improve estimation of DCB values. There are many factors affecting the estimated values of DCBs. The first one is the observation weighting function which depends on the satellite elevation angle. The second factor is concerned with estimating DCBs using a single GPS station using the Zero Difference DCB Estimation (ZDDCBE) code or using the GPS network used by the MSDCBE code. The third factor is the number of GPS receivers in the network. Results from MSDCBE were evaluated and compared with data from IAACs and other codes like M_DCB and ZDDCBE. The results of weighted (MSDCBE) least squares show an improvement for estimated DCBs, where mean differences from the Center for Orbit Determination in Europe (CODE) (University of Bern, Switzerland) are less than 0.746 ns. DCBs estimated from the GPS network show better agreement with IAAC than DCBs estimated from precise point positioning (PPP), where the mean differences are less than 0.1477 and 1.1866 ns, respectively. The mean differences of computed DCBs improved by increasing the number of GPS stations in the network.</p>https://www.ann-geophys.net/37/1039/2019/angeo-37-1039-2019.pdf |
| spellingShingle | A. A. Elghazouly M. I. Doma A. A. Sedeek Estimating satellite and receiver differential code bias using a relative Global Positioning System network Annales Geophysicae |
| title | Estimating satellite and receiver differential code bias using a relative Global Positioning System network |
| title_full | Estimating satellite and receiver differential code bias using a relative Global Positioning System network |
| title_fullStr | Estimating satellite and receiver differential code bias using a relative Global Positioning System network |
| title_full_unstemmed | Estimating satellite and receiver differential code bias using a relative Global Positioning System network |
| title_short | Estimating satellite and receiver differential code bias using a relative Global Positioning System network |
| title_sort | estimating satellite and receiver differential code bias using a relative global positioning system network |
| url | https://www.ann-geophys.net/37/1039/2019/angeo-37-1039-2019.pdf |
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