Wide-area ionospheric delay model for GNSS users in middle- and low-magnetic-latitude regions

GPS Solutions ◽  
2015 ◽  
Vol 20 (1) ◽  
pp. 9-21 ◽  
Author(s):  
An-Lin Tao ◽  
Shau-Shiun Jan
2018 ◽  
Vol 9 (2) ◽  
pp. 175-182 ◽  
Author(s):  
Weili Zhou ◽  
Shuli Song ◽  
Qinming Chen ◽  
Na Cheng ◽  
Hui Xie

2009 ◽  
Vol 62 (3) ◽  
pp. 543-554 ◽  
Author(s):  
Renato Filjar ◽  
Tomislav Kos ◽  
Serdjo Kos

Ionospheric delay is the major source of satellite positioning system performance degradation. Designers of satellite positioning systems attempt to mitigate the impact of the ionospheric delay by deployment of correction models. For instance, the American GPS utilises a global standard (Klobuchar) model, based on the assumption that the daily distribution of GPS ionospheric delay values follows a biased cosine curve during day-time, while during the night-time the GPS ionospheric delay remains constant. Providing a compromise between computational complexity and accuracy, the Klobuchar model is capable of correcting up to 70% of actual ionospheric delay, mainly during quiet space weather conditions. Unfortunately, it provides a very poor performance during severe space weather, geomagnetic and ionospheric disturbances. In addition, a global approach in Klobuchar model development did not take into account particularities of the local ionospheric conditions that can significantly contribute to the general GPS ionospheric delay. Current research activities worldwide are concentrating on a better understanding of the observed GPS ionospheric delay dynamics and the relation to local ionosphere conditions.Here we present the results of a study addressing daily GPS ionospheric delay dynamics observed at a Croatian coastal area of the northern Adriatic (position ϕ=45°N, λ=15°E) in the periods of quiet space weather in 2007. Daily sets of actual GPS ionospheric delay values were assumed to be the time series of composite signals, consisting of DC, cosine and residual components, respectively. Separate models have been developed that describe components of actual GPS ionospheric delay in the northern Adriatic for summer and winter, respectively. A special emphasis was given to the statistical description of the residual component of the daily distribution of GPS ionospheric delay, obtained by removing DC (bias) and cosine components from the composite GPS ionospheric delay.Future work will be focused on further evaluation and validation of a quiet space weather GPS ionospheric delay model for the northern Adriatic, transition to a non-Klobuchar model, and on research in local GPS ionospheric delay dynamics during disturbed and severe space weather conditions.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2845
Author(s):  
Janina Boisits ◽  
Marcus Glaner ◽  
Robert Weber

Propagation delays of GNSS signals caused by the ionosphere can range up to several meters in zenith direction and need to be corrected. Geodetic receivers observing at two or more frequencies allow the mitigation of the ionospheric effects by forming linear combinations. However, single frequency users depend on external information. The ionosphere delay model Regiomontan developed at TU Wien is a regional ionospheric delay model providing high accuracy information with a latency of only a few hours. The model is based on dual-frequency phase observations of a regional network operated by EPOSA (Echtzeit Positionierung Austria) and partners. The corrections cover a geographical extent for receiver positions within Austria and are provided in the standardized IONEX format. The performance of Regiomontan as well as its application in Precise Point Positioning (PPP) were tested with our in-house PPP software raPPPid using the so-called uncombined model with ionospheric constraint. Various tests, e.g., analyzing the coordinate convergence behavior or the difference between estimated and modeled ionospheric delay, proving the high level of accuracy provided with Regiomontan. We conclude that Regiomontan performs at a similar level of accuracy as IGS final TEC maps, but with explicitly reduced latency.


Radio Science ◽  
2004 ◽  
Vol 39 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
L. Sparks ◽  
A. Komjathy ◽  
A. J. Mannucci

2016 ◽  
Vol 5 (4) ◽  
pp. 213-219
Author(s):  
Hyoungmin So ◽  
Jaegyu Jang ◽  
Kihoon Lee ◽  
Kiwon Song ◽  
Junpyo Park

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