Ground- and space-based GPS data ingestion into the NeQuick model

Brunini, C.; Azpilicueta, F.; Gende, Mauricio; Camilion, Emilio; Angel, Aragon; Hernández‐Pajares, M.; Juan, Miao; Sanz, J.; Salazar, Dagoberto

doi:10.1007/s00190-011-0452-4

Cited by 24 publications

(22 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We can identify methods modifying the coefficients of an empirical model (see Brunini et al, 2011;Galkin et al, 2012), methods updating the model towards the measurements without modification of its coefficients (seeods combining both (see Pezzopane et al, 2011) and approaches using physical background models and including the estimation of ionospheric drivers, such as neutral winds, in the state vector (see Schunk et al, 2004;Scherliess et al, 2009;Wang et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Tomography of the ionospheric electron density with geostatistical inversion

et al. 2015

View full text Add to dashboard Cite

Abstract. In relation to satellite applications like global navigation satellite systems (GNSS) and remote sensing, the electron density distribution of the ionosphere has significant influence on trans-ionospheric radio signal propagation. In this paper, we develop a novel ionospheric tomography approach providing the estimation of the electron density's spatial covariance and based on a best linear unbiased estimator of the 3-D electron density. Therefore a non-stationary and anisotropic covariance model is set up and its parameters are determined within a maximum-likelihood approach incorporating GNSS total electron content measurements and the NeQuick model as background. As a first assessment this 3-D simple kriging approach is applied to a part of Europe. We illustrate the estimated covariance model revealing the different correlation lengths in latitude and longitude direction and its non-stationarity. Furthermore, we show promising improvements of the reconstructed electron densities compared to the background model through the validation of the ionosondes Rome, Italy (RO041), and Dourbes, Belgium (DB049), with electron density profiles for 1 day.

show abstract

Section: Introductionmentioning

confidence: 99%

Tomography of the ionospheric electron density with geostatistical inversion

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Possible solutions for that issue might be preconditioning of the NeQuick model (or general background model) by means of the mea- sured STEC or the F2 layer characteristics (e.g. Nava et al, 2006;Brunini et al, 2011) or the combination of different, independent background models (e.g. Elvidge et al, 2016).…”

Section: Simulation Resultsmentioning

confidence: 99%

Ionospheric tomography by gradient-enhanced kriging with STEC measurements and ionosonde characteristics

et al. 2016

View full text Add to dashboard Cite

Abstract. The estimation of the ionospheric electron density by kriging is based on the optimization of a parametric measurement covariance model. First, the extension of kriging with slant total electron content (STEC) measurements based on a spatial covariance to kriging with a spatialtemporal covariance model, assimilating STEC data of a sliding window, is presented. Secondly, a novel tomography approach by gradient-enhanced kriging (GEK) is developed. Beyond the ingestion of STEC measurements, GEK assimilates ionosonde characteristics, providing peak electron density measurements as well as gradient information. Both approaches deploy the 3-D electron density model NeQuick as a priori information and estimate the covariance parameter vector within a maximum likelihood estimation for the dedicated tomography time stamp. The methods are validated in the European region for two periods covering quiet and active ionospheric conditions. The kriging with spatial and spatial-temporal covariance model is analysed regarding its capability to reproduce STEC, differential STEC and foF2. Therefore, the estimates are compared to the NeQuick model results, the 2-D TEC maps of the International GNSS Service and the DLR's Ionospheric Monitoring and Prediction Center, and in the case of foF2 to two independent ionosonde stations. Moreover, simulated STEC and ionosonde measurements are used to investigate the electron density profiles estimated by the GEK in comparison to a kriging with STEC only. The results indicate a crucial improvement in the initial guess by the developed methods and point out the potential compensation for a bias in the peak height hmF2 by means of GEK.

show abstract

“…The evolution of the SIRGAS ionospheric model has been reported in Brunini et al (2011a) and(2011b). Those papers may be useful to clarify some points that are briefly presented in the following two sections.…”

Section: Introductionmentioning

confidence: 97%

“…: Hernández-Pajarez et al 2009), SIRGAS maps were originally based on the so called thin layer ionospheric model (Brunini et al 2011b). According to this model, the vertical structure of the ionosphere (from about 50 to 1,000 km above the Earth´s surface), is approximated with a spherical shell of infinitesimal thickness with equivalent vTEC (located somewhere between 350 and 450 km height).…”

Section: Introductionmentioning

confidence: 99%

Improving SIRGAS Ionospheric Model

Brunini

Azpilicueta

Gende

et al. 2012

Reference Frames for Applications in Geosciences

Self Cite

View full text Add to dashboard Cite

The IAG Sub-Commission 1.3b, SIRGAS (Sistema de Referencia Geocéntrico para las Américas), operates a service for computing regional ionospheric maps based on GNSS observations from its Continuously Operating Network (SIRGAS-CON). The ionospheric model used by SIRGAS (named La Plata Ionopsheric Model, LPIM), has continuously evolved from a "thin layer" simplification for computing the vTEC distribution to a formulation that approximates the electron density (ED) distributions of the E, F1, F2 and top-side ionospheric layers.This contribution presents the newest improvements in the model formulation and validates the obtained results by comparing the computed vTEC to experimental values provided by the ocean altimetry Jason 1 mission. Comparisons showed a small underestimation of the Jason 1 vTEC by about 1.3 TECu on average and rather small differences ranging from À0.5 to À3.4 TECu (at 95 % probability level). The results are encouraging given that comparisons were made in the open ocean regions (far away from the SIRGAS-CON stations).

show abstract

Ground- and space-based GPS data ingestion into the NeQuick model

Cited by 24 publications

References 20 publications

Tomography of the ionospheric electron density with geostatistical inversion

Tomography of the ionospheric electron density with geostatistical inversion

Ionospheric tomography by gradient-enhanced kriging with STEC measurements and ionosonde characteristics

Improving SIRGAS Ionospheric Model

Contact Info

Product

Resources

About