Articles | Volume 9, issue 3
https://doi.org/10.5194/amt-9-1303-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-1303-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Mar 2016
Research article |
| 30 Mar 2016
Statistical framework for estimating GNSS bias
Juha Vierinen
CORRESPONDING AUTHOR
Haystack Observatory, Massachusetts Institute of Technology, Route 40 Westford, 01469 MA, USA
Anthea J. Coster
Haystack Observatory, Massachusetts Institute of Technology, Route 40 Westford, 01469 MA, USA
William C. Rideout
Haystack Observatory, Massachusetts Institute of Technology, Route 40 Westford, 01469 MA, USA
Philip J. Erickson
Haystack Observatory, Massachusetts Institute of Technology, Route 40 Westford, 01469 MA, USA
Johannes Norberg
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
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90 citations as recorded by crossref.
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- 2022 Tonga Volcanic Eruption Induced Global Propagation of Ionospheric Disturbances via Lamb Waves S. Zhang et al. 10.3389/fspas.2022.871275
- Identification of Auroral Zone Activity Driving Large‐Scale Traveling Ionospheric Disturbances L. Lyons et al. 10.1029/2018JA025980
- Multi-instrument study of a spread-F event at Arecibo linked to solar wind variations S. Bostan et al. 10.1016/j.jastp.2023.106099
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- Coupling of Ionospheric Disturbances with Dynamic Processes in the Troposphere G. Golubkov et al. 10.1134/S1990793122030058
- Simultaneous Global Ionospheric Disturbances Associated With Penetration Electric Fields During Intense and Minor Solar and Geomagnetic Disturbances S. Zhang et al. 10.1029/2023GL104250
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- Multi-Instrument Study of a Spread-F Event at Arecibo Linked to Solar Wind Variation S. Bostan et al. 10.2139/ssrn.4179673
- Finding multiscale connectivity in our geospace observational system: Network analysis of total electron content R. McGranaghan et al. 10.1002/2017JA024202
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- The Influence of Tropospheric Processes on Disturbances in the D and E Ionospheric Layers O. Borchevkina et al. 10.3390/atmos12091116
- Assessment of Using Field‐Aligned Currents to Drive the Global Ionosphere Thermosphere Model: A Case Study for the 2013 St Patrick’s Day Geomagnetic Storm Q. Zhu et al. 10.1029/2022SW003170
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- Low- and Mid-Latitude Ionospheric Response to the 2013 St. Patrick’s Day Geomagnetic Storm in the American Sector: Global Ionosphere Thermosphere Model Simulation Q. Zhu et al. 10.3389/fspas.2022.916739
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- CIPS Observations of Gravity Wave Activity at the Edge of the Polar Vortices and Coupling to the Ionosphere V. Harvey et al. 10.1029/2023JD038827
- Subauroral and Polar Traveling Ionospheric Disturbances During the 7–9 September 2017 Storms S. Zhang et al. 10.1029/2019SW002325
- Early Morning Equatorial Ionization Anomaly From GOLD Observations F. Laskar et al. 10.1029/2019JA027487
- First Observations of Large Scale Traveling Ionospheric Disturbances Using Automated Amateur Radio Receiving Networks N. Frissell et al. 10.1029/2022GL097879
- Validating Ionospheric Models Against Technologically Relevant Metrics A. Chartier et al. 10.1029/2023SW003590
- An Ionosphere Specification Technique Based on Data Ingestion Algorithm and Empirical Orthogonal Function Analysis Method E. Aa et al. 10.1029/2018SW001987
- Model‐Free Approach for Regional Ionospheric Multi‐Instrument Imaging J. Norberg et al. 10.1029/2022JA030794
- Multi-instrument observations of SCIPS: 1. ISR and GPS TEC results R. Dinsmore et al. 10.1016/j.jastp.2020.105515
- A Comparison of the Location of the Mid‐Latitude Trough and Plasmapause Boundary J. Weygand et al. 10.1029/2020JA028213
- Multi-instrumental analysis of the day-to-day variability of equatorial plasma bubbles E. Aa et al. 10.3389/fspas.2023.1167245
- Polar Vortex Strength Impacts on the Longitudinal Structure of Thermospheric Composition and Ionospheric Electron Density K. Greer et al. 10.1029/2023JA031797
- Observations of Night‐Time Equatorial Ionosphere Structure With the FPMU on Board the International Space Station A. Newheart et al. 10.1029/2022JA030373
- Estimation of Ionospheric Total Electron Content From a Multi-GNSS Station in China C. She et al. 10.1109/TGRS.2019.2941049
- Traveling Ionospheric Disturbances in the Vicinity of Storm‐Enhanced Density at Midlatitudes S. Zhang et al. 10.1029/2022JA030429
- GCP and PPK Utilization Plan to Deal with RTK Signal Interruption in RTK-UAV Photogrammetry J. Cho & B. Lee 10.3390/drones7040265
- Extreme Low‐Latitude Total Electron Content Enhancement and Global Positioning System Scintillation at Dawn S. Mrak et al. 10.1029/2021SW002740
- Characterizing the Complex Two N‐Wave Ionospheric Signature of the 2016 Kaikoura Earthquake J. Li et al. 10.1029/2018JA025376
- Two‐Dimensional Reconstruction of Ionospheric Plasma Density Variations Using Swarm A. Fæhn Follestad et al. 10.1029/2019SW002406
- Direct Connection Between Auroral Oval Streamers/Flow Channels and Equatorward Traveling Ionospheric Disturbances L. Lyons et al. 10.3389/fspas.2021.738507
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Saved (preprint)
Latest update: 23 Apr 2024
Short summary
We present a statistical framework for estimating GNSS receiver bias by using a weighted linear least squares of independent differences (WLLSID) model to examine differences of a large number of TEC measurements. This allows a consistent way for treating elevation-dependent model errors and spatiotemporal distance-dependent geophysical differences arising in ionospheric GNSS measurements. The method is also applicable to other GNSS system than GPS, supporting, e.g., GLONASS.
We present a statistical framework for estimating GNSS receiver bias by using a weighted linear...
