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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/angeo-2018-120
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-2018-120
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular paper 03 Dec 2018

Regular paper | 03 Dec 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Annales Geophysicae (ANGEO).

Estimating Satellite and Receiver Differential Code Bias Using Relative GPS Network

Alaa A. Elghazouly1, Mohamed I. Doma1, and Ahmed A. Sedeek2 Alaa A. Elghazouly et al.
  • 1Faculty of Engineering, Menoufia University, Egypt
  • 2EL Behira Higher Institute of Engineering and Technology, El Behira, Egypt

Abstract. Precise Total Electron Content (TEC) are required to produce accurate spatial and temporal resolution of Global Ionosphere Maps (GIMs). Receivers and Satellites Differential Code Biases (DCBs) are one of the main error sources in estimating precise TEC from Global Positioning Systems (GPS) data. Recently, researchers are interested in developing models and algorithms to compute DCBs of receivers and satellites close to those computed from the Ionosphere Associated Analysis Centers (IAAC). Here we introduce a MATLAB code called Multi Station DCB Estimation (MSDCBE) to calculate satellites and receivers DCBs from GPS data. MSDCBE based on spherical harmonic function and geometry free combination of GPS carrier phase and pseudo-range code observations and weighted least square were applied to solve observation equations, to improve estimation of DCBs values. There are many factors affecting estimated value of DCBs. The first one is the observations weighting function which depending on the satellite elevation angle. The second factor concerned with estimating DCBs using single GPS Station Precise Point Positioning (PPP) or using GPS network. The third factor is the number of GPS receivers in the network. Results from MSDCBE were evaluated and compared with data from IAAC and other codes like M_DCB and ZDDCBE. The results of weighted (MSDCBE) least square shows an improvement for estimated DCBs, where mean differences from CODE less than 0.746ns. DCBs estimated from GPS network shows a good agreement with IAAC than DCBs estimated from PPP where the mean differences are less than 0.1477ns and 1.1866ns, respectively. The mean differences of computed DCBs improved by increasing number of GPS stations in the network.

Alaa A. Elghazouly et al.
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Alaa A. Elghazouly et al.
Alaa A. Elghazouly et al.
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Receivers and Satellites Differential Code Biases (DCBs) are one of the main error sources in estimating precise Global Ionosphere Maps (GIMs) from Global Positioning Systems (GPS) data. This paper introduces a mathematical model for estimating satellites & receivers DCBs from A GPS network written under MATLAB environment. Our code was tested and compared with Ionosphere Associated Analysis Centers (IAAC) and other researchers' codes results. The results shows an improvement for estimated DCBs.
Receivers and Satellites Differential Code Biases (DCBs) are one of the main error sources in...
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