EGNOS test bed ionospheric corrections under the October and November 2003 storms

Hernández‐Pajares, M.; Zornoza, José Miguel Juan; Subirana, Jaume Sanz; Farnworth, Richard; Soley, Santiago

doi:10.1109/tgrs.2005.855625

Cited by 26 publications

(15 citation statements)

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“…While more sites were available at that time, not all sites were used, as the main aim of this paper is to examine interpolation during high-sparsity cases. The time period over which data were drawn was from noon to midnight on October 30, 2003-the peak of the much studied "Halloween Storm" [49]. Data were considered stationary within 15-min intervals and projected onto a "thin shell" for reconstruction [47].…”

Section: B Tec Data Resultsmentioning

confidence: 99%

An Evaluation of Interpolation Techniques for Reconstructing Ionospheric TEC Maps

Foster

Evans

2008

IEEE Trans. Geosci. Remote Sensing

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Maps of the total electron content (TEC) of the ionosphere can be reconstructed using data extracted from global positioning system (GPS) signals. For historic and other sparse data sets, the reconstruction of TEC images is often performed using a multivariate interpolation technique. Although there are many interpolation methods available, only a limited number, for example kriging, have been applied to TEC data. This paper presents a quantitative comparison of various commonly used algorithms for scattered-data interpolation over a range of sparsities. Techniques evaluated include a relatively new approach called Adaptive Normalized Convolution (ANC) that has not previously been applied to ionospheric reconstruction. The proposed evaluation scheme employs a quantitative methodology applied to both simulated and real TEC data. Results show that, although the performance of kriging is good in many cases, it is several times worse than the best performing techniques at some sparsities. Natural-neighbor interpolation has a better overall performance than kriging for both simulated and TEC data. Although its performance is a few percent worse than other methods for the simulated data, ANC produces the best performance for the TEC reconstructions. He has published over 50 papers in journals and refereed conference proceedings. His current research interests include nonlinear image processing, feature extraction and motion estimation in application to remotely sensed, color and multispectral images, and video compression.

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Section: B Tec Data Resultsmentioning

confidence: 99%

An Evaluation of Interpolation Techniques for Reconstructing Ionospheric TEC Maps

Foster

Evans

2008

IEEE Trans. Geosci. Remote Sensing

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“…For instance, the ionosphere, that is the part of the atmosphere above 60 km until 2000 km of the Earth surface, is a plasmatic medium that causes a slow down in the group velocity and a speed up of the phase velocity, having an impact in code and phase delays and, thus, impeding precise navigation when its effects are not mitigated. Actually, errors can be on the order of tens of meters in geomagnetic storm episodes [2]. Ionospheric delay is a well-defined function proportional to the inverse square of frequency and the total electron content (TEC) -which has diurnal, seasonal and long-term variations -along the signal path.…”

Section: Fundamentals Of Global Navigation Satellite Systemsmentioning

confidence: 99%

Multipath estimating tracking loops in advanced GNSS receivers with particle filtering

Closas

Fernández‐Prades

Díez³

et al. 2012

2012 IEEE Aerospace Conference

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This paper studies Bayesian filtering techniques applied to the design of advanced delay/phase tracking loops in GNSS receivers, which estimate not only direct path parameters but those of multipath. The analysis includes trade-off among realistic propagation channel models and the use of a realistic simulation framework. The proposed filtering technique implements Rao-Blackwellization of linear states and a particle filter for the nonlinear partition. Computer simulations highlight the superior performance of such method when compared to traditional DLL/PLL based schemes, approaching theoretical limits.

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“…The common method, which is usually utilized in the Wide Area Differential GPS System (WADGPS), is estimating the ionosphere corrections on some pre-defined Ionosphere Grid Points (IGP). The user terminal receives these corrections and use them to reduce the ionosphere effect [2,3].The ionosphere correcting performance is dependent on the accuracy of the estimating method. The traditional method for estimating the ionosphere corrections is based on the weighted Least Square algorithm.…”

Section: Introductionmentioning

confidence: 99%

The high-accuracy ionosphere correcting algorithm for GNSS signals based on kalman filter

Gao

Hong

Gao

et al. 2011

IEICE Electron. Express

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A filter-based algorithm for estimating the ionosphere error of the GNSS signals in the differential system is proposed in the paper. Based on the slow-varying characteristic of the ionosphere delay, the historical ionosphere delay data is involved in the algorithm. The measurement model is constructed according to the Grid Interpolation Model (GIM).The relevant analysis is conducted by the simulation and the corresponding results indicated that comparing with the traditional method, at least 60% promotion on the accuracy has been accomplished so that the algorithm in this paper can provide a more accurate estimation of the ionosphere error for GNSS signals.

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EGNOS test bed ionospheric corrections under the October and November 2003 storms

Cited by 26 publications

References 1 publication

An Evaluation of Interpolation Techniques for Reconstructing Ionospheric TEC Maps

An Evaluation of Interpolation Techniques for Reconstructing Ionospheric TEC Maps

Multipath estimating tracking loops in advanced GNSS receivers with particle filtering

The high-accuracy ionosphere correcting algorithm for GNSS signals based on kalman filter

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