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Total electron content processing from GPS observations to facilitate ionospheric modeling

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Abstract

With the increasing global distribution of high rate dual-frequency global positioning system (GPS) receivers, the production of a real-time atmospheric constituent definition, total electron content (TEC), has become a beneficial contributor to the modeling applications used in the assessment of GPS position accuracy and the composition of the ionosphere, plasmasphere, and troposphere. Historically, TEC measurements have been obtained through post processing techniques to produce the quality of data necessary for modeling applications with rigorous error estimate requirements. These procedures necessitated the collection of large volumes of data to address the various abnormalities in the computation of TEC associated with the use of greater data quality controls and source selection while real-time modeling environments must rely on autonomous controls and filtration techniques to prevent the production of erroneous model results. In this paper we present methods for processing TEC in real time, which utilize several procedures including the application of an ionospheric model to automatically perform quality control on the TEC output and the computational techniques used to address receiver multipath, faulty receiver observations, cycle-slips, segmented processing, and receiver calibrations. The resulting TEC measurements are provided with rigorous error estimates validated using the vertical TEC from the Jason satellite mission.

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Abbreviations

GPS:

Global positioning system

TEC:

Total electron content

CDDIS:

Crustal dynamics data information system

RINEX:

Receiver independent exchange

CODE:

Center for Orbit Determination in Europe

IPP:

Ionospheric penetration point

UHF:

Ultra-high frequency

PIM:

Parameterized ionospheric model

URSI:

Union of radio science

IQR:

Interquartile range

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Acknowledgments

The authors are grateful to all colleagues of the Communication/Navigation Outage Forecasting System team and the Air Force Research Laboratory for providing valuable discussions and suggestions. We thank Dr. Laila S. Jeong for encouraging the implementation of this research and Dr. Brian Wilson of the Jet Propulsion Laboratory for providing the Jason TEC.

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  1. AER Inc., 131 Hartwell Ave, Lexington, MA, 02421-3126, USA

    Angeline G. Burrell, Nelson A. Bonito & Charles S. Carrano

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  1. Angeline G. Burrell
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  2. Nelson A. Bonito
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  3. Charles S. Carrano
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Correspondence to Angeline G. Burrell.

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Burrell, A.G., Bonito, N.A. & Carrano, C.S. Total electron content processing from GPS observations to facilitate ionospheric modeling. GPS Solut 13, 83–95 (2009). https://doi.org/10.1007/s10291-008-0102-3

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