SIMuRG: System for Ionosphere Monitoring and Research from GNSS

Yasyukevich, Yury; Kiselev, Alexander V.; Zhivetiev, I. V.; Edemskiy, Ilya; Syrovatskii, S.; Maletckii, Boris; Vesnin, Artem

doi:10.1007/s10291-020-00983-2

Cited by 37 publications

(26 citation statements)

References 52 publications

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“…The first way includes spline detrending and CMA filtering (dTEC detr ), while the second one includes only CMA filtering (dTEC nodetr ). We used GPS/GLONASS data from 3532 stations from the SIMuRG [15] database for 21 February 2019. The total number of TEC series was 169,731.…”

Section: Discussionmentioning

confidence: 99%

“…Unfortunately, the STFT approach cannot always be used for several algorithms applied now, such as interferometry [13], or solar flare effect detection [14]. Our own experience showed that the artifacts originating from inaccurate filtering might impact upon processing results interpretation, particularly at automatic processing, such as SIMuRG [15]. Therefore, correct filtration is a critical for GNSS automatic data treatment techniques.…”

Section: Introductionmentioning

confidence: 99%

“…We are planning to incorporate above suggestion to systems for automatic treatment, like SIMuRG (https://simurg.iszf.irk.ru) [15].…”

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confidence: 99%

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Wave Signatures in Total Electron Content Variations: Filtering Problems

2020

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Over recent years, global navigation satellite systems (GNSSs) have been increasingly used to study near-Earth space. The basis for such studies is the total electron content (TEC) data. Standard procedures for detecting TEC wave signatures include variation selection and detrending. Our experience showed that the inaccurate procedure causes artifacts in datasets which might affect data interpretation, particularly in automated processing. We analyzed the features of various detrending and variation selection methods. We split the problem of the GNSS data filtering into two subproblems: detrending and variation selection. We examined centered moving average, centered moving median, 6th-order polynomial, Hodrick–Prescott filter, L1 filter, cubic smoothing spline, double-applied moving average for the GNSS-TEC detrending problem, and centered moving average, centered moving median, Butterworth filter, type I Chebyshev filter for the GNSS-TEC variation selection problem in this paper. We carried out the analysis based on both model and experimental data. Modeling was based on simple analytical models as well as the International Reference Ionosphere. Analysis of TEC variations of 2–10 min, 10–20 min, and 20–60 min under insufficient detrending conditions showed that the higher errors appear for the longer periods (20–60 min). For the detrending problem, the smoothing cubic spline provided the best results among the algorithms discussed in this paper. The spline detrending featured the minimal value of the mean bias error (MBE) and the root-mean-square error (RMSE), as well as high correlation coefficient. The 6th-order polynomial also produced good results. Spline detrending does not introduce a RMSE more than 0.25 TECU and MBE > 0.35 TECU for IRI trends, while, for the 6th-order polynomial, these errors can exceed 1 TECU in some cases. However, in 95% of observations the RMSE and MBE do not exceed 0.05 TECU. For the variation selection, the centered moving average filter showed the best performance among the algorithms discussed in this paper.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wave Signatures in Total Electron Content Variations: Filtering Problems

2020

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“…Panels a and b in the figure show the intensity in total electron content (TEC) variations filtered within 10-20 min range at the corresponding time instants. These variations are obtained using the SIMuRG tool for collecting, processing, storage and presentation of GNSS TEC data [9].…”

Section: Geomagnetic Storm Of August 25-26 2018mentioning

confidence: 99%

Changes in the GNSS precise point positioning accuracy during a strong geomagnetic storm

2020

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Based on the data from dual-frequency receivers of global navigation satellite systems (GNSS), we analyze the changes in GNSS positioning accuracy during the August 25-26, 2018 strong geomagnetic storm on a global scale. The storm is one of the strongest geomagnetic events of the solar cycle 24. To analyze the positioning quality, we calculated coordinates using the precise point positioning (PPP) method in the kinematic mode. We recorder a significant degradation in the PPP positioning accuracy during the main phase of the storm. The maximum effect is observed in the middle and high latitudes of the US-Atlantic longitude sector. The average PPP error during the storm is shown to exceed ~0.5 m, that is up to 5 times higher than the values typical on quiet days. Areas with increased PPP errors is revealed to correspond to the regions with significant increase in the intensity of total electron content variations of 10–20 min period range. This increase is presumably due to the auroral oval expansion toward middle latitudes.

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“…We marked each ionospheric pierce point (at 300 km height) with the color corresponding to the TEC variation value. All calculations of TEC variations were performed by SIMuRG (https://simurg.iszf.irk.ru) [47].…”

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Small-Scale Ionospheric Irregularities of Auroral Origin at Mid-latitudes during the 22 June 2015 Magnetic Storm and Their Effect on GPS Positioning

et al. 2020

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Small-scale ionospheric irregularities affect navigation and radio telecommunications. We studied small-scale irregularities observed during the 22 June 2015 geomagnetic storm and used experimental facilities at the Institute of Solar-Terrestrial Physics of the Siberian Branch of the Russian Academy of Sciences (ISTP SB RAS) located near Irkutsk, Russia (~52°N, 104°E). The facilities used were the DPS-4 ionosonde (spread-F width), receivers of the Irkutsk Incoherent Scatter Radar (Cygnus A signal amplitude scintillations), and GPS/GLONASS receivers (amplitude and phase scintillations), while 150 MHz Cygnus A signal recording provides a unique data set on ionosphere small-scale structure. We observed increased spread-F, Cygnus A signal amplitude scintillations, and GPS phase scintillations near 20 UT on 22 June 2015 at mid-latitudes. GPS/GLONASS amplitude scintillations were at a quiet time level. By using global total electron content (TEC) maps, we conclude that small-scale irregularities are most likely caused by the auroral oval expansion. In the small-scale irregularity region, we recorded an increase in the precise point positioning (PPP) error. Even at mid-latitudes, the mean PPP error is at least five times that of the quiet level and reaches 0.5 m.

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SIMuRG: System for Ionosphere Monitoring and Research from GNSS

Cited by 37 publications

References 52 publications

Wave Signatures in Total Electron Content Variations: Filtering Problems

Wave Signatures in Total Electron Content Variations: Filtering Problems

Changes in the GNSS precise point positioning accuracy during a strong geomagnetic storm

Small-Scale Ionospheric Irregularities of Auroral Origin at Mid-latitudes during the 22 June 2015 Magnetic Storm and Their Effect on GPS Positioning

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