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GPS Instrumental Biases Estimation Using Continuous Operating Receivers Network
Alaa Elghazouly, Mohamed Doma, Ahmed Sedeek
Pages - 1 - 12     |    Revised - 31-01-2019     |    Published - 28-02-2019
Volume - 6   Issue - 1    |    Publication Date - February 2019  Table of Contents
DCBs, IBs, Multi Station, Elevation Angle, Total Electron Content.
Precise Total Electron Content (TEC) are required to produce accurate spatial and temporal resolution of Global Ionosphere Maps (GIMs). Receivers and Satellites Instrumental Biases (IBs) 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 IBs of receivers and satellites close to those computed from the Ionosphere Associated Analysis Centers (IAAC). Here we introduce a MATLAB code called Multi Station IBs Estimation (MSIBE) to calculate satellites and codeless tracking receivers IBs from GPS data. MSIBE 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 IBs values. There are many factors affecting estimated value of IBs. The premier factor is the observations weighting function which relying on the satellite elevation angle. The second factor concerned with estimating IBs 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 MSIBE were evaluated and compared with data from IAAC and other codes like M_DCB and ZDDCBE. The results of weighted (MSIBE) least square shows an improvement for estimated IBs, where mean differences from CODE less than 0.746 ns. IBs estimated from Continuous Operating Receivers (CORs) GPS network shows a good agreement with IAAC than IBs estimated from PPP where the mean differences are less than 0.1477 ns and 1.1866 ns, respectively. The mean differences of computed IBs improved by increasing number of GPS stations in the network.
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3 ResearchGate 
4 Doc Player 
5 Scribd 
6 SlideShare 
1 Böhm, J., and Schuh, H.: Atmospheric Effects in Space Geodesy, Springer Atmospheric Sciences, eBook ISBN :978-3-642-36932-2, (2013).
2 Hernández-Pajares, M., Juan, J., Sanz, J.: New approaches in global ionospheric determination using ground GPS data. Atmos Solar Terr Phys 61:1237-1247, (1999).
3 Komjathy, A., Sparks, L., Wilson, BD., Mannucci, AJ.: Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms. Radio Sci (2005), https://doi:10.1029/2005RS003279.
4 Li, Z., Yuan, Y., Wang, N., Hernandez-Pajares, M., and Huo, X.: SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions, J Geodesy 89(4):331-345, (2015).
5 Liu, Z., and Gao,Y.: Ionospheric TEC predictions over a local area GPS reference network, GPS Solut 8:23-29, (2004).
6 Mannucci, AJ., Wilson, BD., Edwards, CD.: A new method for monitoring the Earth's ionospheric total electron content using the GPS global network. In: Proceedings of ION GPS-93, the 6th international technical meeting of the satellite division of The Institute of Navigation, Salt Lake City, UT, 22-24 September 1993, pp 1323-1332, (1993).
7 McCaffrey, A., Jayachandran, P., Themens, D., and Langley, R.: GPS receiver code bias estimation: A comparison of two methods. Elsevier, Advances in Space Research 59 1984-1991, (2017).
8 Arikan, F., Nayir, H., Sezen, U., Arikan, O.: Estimation of single station interfrequency receiver bias using GPS-TEC, Radio Sci. 43 (4). http://dx.doi.org/10.1029/2007rs003785, (2008).
9 Themens, D.R., Jayachandran, P.T., Langley, R.B., MacDougall, J.W., Nicolls, M.J.: Determining receiver biases in GPS-derived total electron content in the auroral oval and polar cap region using ionosonde measurements, GPS Solut. 17 (3), 357-369, (2013).
10 Themens, D.R., Jayachandan, P.T., Langley, R.B.: The nature of GPS differential receiver bias variability: An examination in the polar cap region, J. Geophys. Res.: Space Phys. 120 (9), 8155-8175, (2015).
11 Sedeek, A., Doma, M., Rabah, M., and Hamama, M.: Determination of zero difference GPS differential code biases for satellites and prominent receiver types, Arab J Geosci, DOI 10.1007/s12517-017-2835-1, (2017).
12 Schaer, S.: Mapping and predicting the earth's ionosphere using global positioning system, Ph.D. dissertation, Astronomy Institute, University Bern, Switzerland, 205 pp, (1999).
13 Feltens, J., and Schaer, S.: IGS Products for the Ionosphere, Proceedings of the 1998 IGS Analysis Center Workshop Darmstadt, Germany, (1998).
14 Mannucci, A., Wilson, B., Yuan, D., Ho, C., Lindqwister, U., and Runge, T.: Global mapping technique for GPS-derived ionospheric total electron content measurements, RadioSci.33(3),565-582, (1998).
15 Orús,R., Hernández-Pajares, M., Juan, J., and Sanz, J.: Improvement of global ionospheric VTEC maps by using kriging interpolation technique, J.Atmos.Sol.Terr.Phys.67(16),1598-1609, (2005).
16 Jin, S., Luo, O., and Park, P.: GPS observations of the ionospheric F2-layer behavior during the 20th November 2003 geomagnetic storm over South Korea, Journal of Geodesy, 82(12):883-892, (2008).
17 Leandro, R.: Precise Point Positioning with GPS: A New Approach for Positioning, Atmospheric Studies, and Signal Analysis, Ph.D. dissertation, Department of Geodesy and Geomatics Engineering, Technical Report No. 267, University of New Brunswick, Fredericton, New Brunswick, Canada, 232 pp, (2009).
18 Leick, A., Rapoport, L., and Tatarnikov, D.: GPS satellite surveying, Wiley, New York, (2015).
19 Zhang, B., Peter, J. G., Teunessen, Y., Hongxing, Z., and Min, L.: "Joint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBs) using low-cost receivers" J. Geod. 92: 401-413, 2018.
20 Al-Fanek, O.: Ionospheric Imaging for Canadian Polar Regions, PhD thesis, Calgary, Alberta, (2013).
21 Jin, R., Jin, S., and Feng, G.: M_DCB: MATLAB code for estimating GPS satellite and receiver differential code biases, GPS Solution 16:541-548, (2012).
22 Hansen, A.: Tomographic Estimation of the Ionosphere Using GPS Sensors, PhD Thesis, Department of Electrical Engineering, Stanford University, CA, (2002).
23 Abid, M., Mousa, A., Rabah, M., El mewafi, M., and Awad, A.: Temporal and spatial variation of differential code biases: A case study of regional network in Egypt, Alexandria Engineering Journal, 55, 1507-1514, 2016.
24 Haines, G.: Spherical cap harmonic analysis, J Geophys Res Solid Earth 1985;90(B3):2583e91, 1985.
25 Ghilani, C., and Wolf, P.: Elementary surveying: an introduction to geomatics-13th ed, 2012.
26 Luo, X.: GPS Stochastic Modelling: Signal Quality Measures and ARMA Processes, PhD thesis, the Karlsruhe Institute of Technology, Karlsruhe, Germany, 2013.
Dr. Alaa Elghazouly
Faculty of Engineering, Civil Engineering, Menoufia University - Egypt
Dr. Mohamed Doma
Faculty of Engineering, Civil Engineering, Menoufia University - Egypt
Dr. Ahmed Sedeek
Higher Institute of Engineering and Technology, Civil Department, El Behira, Egypt - Egypt