Real-time interpolation of global ionospheric maps by means of sparse representation

Yang, Heng; Monte, Enric; Hernández‐Pajares, M.; Roma-Dollase, David

doi:10.1007/s00190-021-01525-5

Cited by 22 publications

(23 citation statements)

References 33 publications

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“…1. To investigate the possibility and reliability of monitoring the ionospheric perturbation degree in real-time with the newly developed real-time GIMs (Li et al, 2020;Liu, Hernández-Pajares, Yang, et al, 2021;Yang et al, 2021). 2.…”

Section: Discussionmentioning

confidence: 99%

A New Way of Estimating the Spatial and Temporal Components of the Vertical Total Electron Content Gradient Based on UPC‐IonSAT Global Ionosphere Maps

et al. 2022

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The fluctuations of the ionospheric electron density (i.e., ionosphere perturbations) have adverse impacts on the transionospheric radio signals including radar altimetry, radio communication systems, space-based remote sensing, and Global Navigation Satellite System (GNSS) positioning (e.g., Jakowski, Béniguel, et al., 2012;Jakowski, Borries, & Wilken, 2012;Monaldo, 1991). For example, due to the large fluctuations of the ionospheric electron density, the GPS stations experienced an outage at high latitude, and the Wide Area Augmentation System was disabled for few hours in the United States of America during the Halloween storm of 2003 (Doherty et al., 2004;Webb & Allen, 2004), which also affected to the Test Bed of the European Geostationary Navigation Overlay Service (EGNOS) in northern Europe (Hernández-Pajares et al., 2005). In addition, the EGNOS service was degraded during the ionospheric perturbation period of St. Patrick's Day storm in 2015. Consequently, it is important to identify the perturbation degree of the ionosphere to monitor the ionospheric state.To characterize the amplitude and phase fluctuations of GNSS signals, the ionosphere scintillation index S4 and σ ϕ were introduced in 1981 (Rino et al., 1981). Based on Total Electron Content (TEC) from GNSS receivers, the Rate of Change of TEC Index (ROTI) was proposed as a measure of ionospheric irregularities (Pi et al., 1997). A new ionospheric perturbation index, Regional Ionosphere Disturbances IndeX, was based on regional Neustrelitz TEC Model (Jakowski et al., 2006). With data sets from the European Space Agency (ESA) Swarm constellation, the Ionospheric Bubble Index was generated as a level 2 product to provide information about Equatorial Plasma Bubbles (Park et al., 2013). A global ionospheric disturbance index map, W-index map, use the TEC from Global Ionosphere Map (GIM) refer to the median TEC value of preceding 7 days to

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Section: Discussionmentioning

confidence: 99%

A New Way of Estimating the Spatial and Temporal Components of the Vertical Total Electron Content Gradient Based on UPC‐IonSAT Global Ionosphere Maps

et al. 2022

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“…Additionally, the VTEC interpolation techniques of the UPC RT-TOMION model are performed either by spherical harmonics or Kriging [16] so to fill the gaps where data is lacking. In addition, the most recent maps are interpolated by means of the ADDGIM algorithm presented in [19]. For more details of the processing and interpolation of the GIMs, see [19].…”

Section: Upc-ionsat Real-time Global Ionospheric Maps and Data Prepro...mentioning

confidence: 99%

“…In addition, the most recent maps are interpolated by means of the ADDGIM algorithm presented in [19]. For more details of the processing and interpolation of the GIMs, see [19].…”

Section: Upc-ionsat Real-time Global Ionospheric Maps and Data Prepro...mentioning

confidence: 99%

Forecast of the Global TEC by Nearest Neighbour Technique

2022

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We propose a method for Global Ionospheric Maps of Total Electron Content forecasting using the Nearest Neighbour method. The assumption is that in a database of global ionosphere maps spanning more than two solar cycles, one can select a set of past observations that have similar geomagnetic conditions to those of the current map. The assumption is that the current ionospheric condition can be expressed by a linear combination of conditions seen in the past. The average of these maps leads to common geomagnetic components being preserved and those not shared by several maps being reduced. The method is based on searching the historical database for the dates of the maps closest to the current map and using as a prediction the maps in the database that correspond to time shifts on the prediction horizons. In contrast to other methods of machine learning, the implementation only requires a distance computation and does not need a previous step of model training and adjustment for each prediction horizon. It also provides confidence intervals for the forecast. The method has been analyzed for two full years (2015 and 2018), for selected days of 2015 and 2018, i.e., two storm days and two non-storm days and the performance of the system has been compared with CODE (24- and 48-h forecast horizons).

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“…The labels "uadg" and "rt_casg" refer to the real-time UPC and CAS products, "othg" and "uqrg" stand for the ultra-rapid DGFI-TUM product and the rapid UPC product. use of Kriging interpolation and the real-time product "uadg" employs a method called Atomic Decomposition Interpolator of GIMs (ADIGIM); see, for example, Yang et al (2021).…”

Section: External Quality Assessment Of the Real-time Vtec Productsmentioning

confidence: 99%

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

Erdogan¹,

Schmidt²,

Goss³

et al. 2021

Space Weather

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Real-time monitoring of the ionospheric plasma distribution and associated irregularities is of increasing importance for users of the Global Navigation Satellite Systems (GNSS) in various fields such as telecommunication, positioning, navigation, aviation, natural disaster monitoring and warning. It is also vital to monitor the ionosphere in real-time for forecasting space weather events. Rapid technological advances in the fast transmission of big data allow for generating and disseminating the essential ionosphere parameters, including the spatio-temporal variations of the Vertical Total Electron Content (VTEC), with low latency. The International GNSS Service (IGS) and its Ionosphere Associated Analysis Centers have been continuously providing Global Ionosphere Maps (GIMs) with improving resolution, accuracy, and latency since 1998 (Hernández-Pajares et al., 2009). By following the launch of the experimental IGS International

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Real-time interpolation of global ionospheric maps by means of sparse representation

Cited by 22 publications

References 33 publications

A New Way of Estimating the Spatial and Temporal Components of the Vertical Total Electron Content Gradient Based on UPC‐IonSAT Global Ionosphere Maps

A New Way of Estimating the Spatial and Temporal Components of the Vertical Total Electron Content Gradient Based on UPC‐IonSAT Global Ionosphere Maps

Forecast of the Global TEC by Nearest Neighbour Technique

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

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