Kriging‐based ionospheric TEC, ROTI and amplitude scintillation index (S4) maps for India

Harsha, P. Babu Sree; Ratnam, D. Venkata; Nagasri, Mutyala Lavanya; Sridhar, M.; Raju, K. Padma

doi:10.1049/iet-rsn.2020.0202

Cited by 13 publications

(4 citation statements)

References 56 publications

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“…It is used in the detection and investigation of occurrences of ionospheric irregularities. ROTI was estimated by dual-frequency GNSS data with the time interval of 5 min by using Equation (3) [68][69][70][71][72]:…”

Section: Rot and Rotimentioning

confidence: 99%

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Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision

et al. 2021

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In this work, we present the positioning error analysis of the 12 May 2021 moderate geomagnetic storm. The storm happened during spring in the northern hemisphere (fall in the south). We selected 868 GNSS stations around the globe to study the ionospheric and the apparent position variations. We compared the day of the storm with the three previous days. The analysis shows the global impact of the storm. In the quiet days, 93% of the stations had 3D errors less than 10 cm, while during the storm, only 41% kept this level of accuracy. The higher impact was over the Up component. Although the stations have algorithms to correct ionospheric disturbances, the inaccuracies lasted for nine hours. The most severe effects on the positioning errors were noticed in the South American sector. More than 60% of the perturbed stations were located in this region. We also studied the effects produced by two other similar geomagnetic storms that occurred on 27 March 2017 and on 5 August 2019. The comparison of the storms shows that the effects on position inaccuracies are not directly deductible neither from the characteristics of geomagnetic storms nor from enhancement and/or variations of the ionospheric plasma.

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Section: Rot and Rotimentioning

confidence: 99%

“…The ROT and ROTI values are typically expressed in units of TECu/min. ROT is defined as the TEC variation rate of two successive epochs as stated in Equation ( 4) [68][69][70][71]:…”

Section: Rot and Rotimentioning

confidence: 99%

Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision

et al. 2021

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“…Furthermore, to reduce the impact of multipath, the 20‐degree elevation mask is adopted, which was utilized by previous scintillation investigations (e.g., Béniguel, 2019; Salles et al., 2021; Veettil et al., 2020). Meanwhile, to avoid other nonscintillation‐related disturbances on BDS signals, 0.2 is selected as the threshold of the amplitude scintillation index S 4 indicating the occurrence of ionospheric scintillation at the given epoch (Luo et al., 2020; Muella et al., 2009, 2014; Pasumarthi et al., 2020; Zhao et al., 2022), characterized by the standard deviation of I /, where I is the received signal intensity (power) and < > represents temporal averaging, typically during a 60‐s interval, assuming a sampling frequency of 50 Hz (Luo et al., 2020; Moraes et al., 2019; Song et al., 2022; Sousasantos et al., 2018), to indicate the occurrence of ionospheric scintillation. Ionospheric scintillation events were further classified as weak (0.2 ≤ S 4 < 0.4), moderate (0.4 ≤ S 4 < 0.6), and intense ( S 4 ≥ 0.6) (Humphreys et al., 2010; Vilà‐Valls et al., 2020).…”

Section: Description Of Measurements and Data Processingmentioning

confidence: 99%

Investigating the Effects of Ionospheric Scintillation on Multi‐Frequency BDS‐2/BDS‐3 Signals at Low Latitudes

et al. 2023

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Ionospheric scintillation could seriously disrupt the signal tracking of the global navigation satellite systems (GNSS), further causing positioning accuracy degradation or unavailability. BeiDou navigation satellite system (BDS), a newly developed GNSS by China, has begun to provide global positioning, navigation, and timing service. The objective of the present study is to investigate the effects of ionospheric scintillation on BDS‐2 and BDS‐3 multi‐frequency signals. Ionospheric scintillation monitor receiver data from four monitors in Brazil were collected from October 2021 to May 2022. The results illustrate that S4(B2) and S4(B3) linearly increase with S4(B1) for S4(B1) ≤ 0.6, which is consistent with weak scattering theories, and average experimental ratios of S4(B2)/S4(B1), S4(B3)/S4(B1), and S4(B2)/S4(B3) are less than corresponding theoretical ones by 6.1%, 4.4%, and 1.9%, respectively. Meanwhile, as S4 values increase, lower‐frequency scintillation saturates earlier than higher ones, and the probability of ionospheric scintillation events on B2 and B3 signals is approximately twice (S4 ≥ 0.7) as B1 signals in the equatorial ionization anomaly (EIA) regions. To alleviate the undesirable effects of missing data on GNSS positioning, we first investigate the inter‐frequency relationship and distribution probability of two significant spectral parameters, that is, T (the spectral strength of the phase noise at 1 Hz) and p (the spectral slope of the phase power spectral density) in the tracking jitter model among three BDS frequencies. Results show that the performances among B1, B2, and B3 frequencies have a higher correlation respectively, and their values for B2 and B3 signals are more susceptible to be impacted by ionospheric scintillation.

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“…Typical examples include the use of the spherical harmonics (SH) function (Bilitza et al., 2011) and spherical radial basis function (SRBF) (Khoshgovari et al., 2020) to achieve TEC reconstruction in the global and Iranian regions, respectively. Commonly used spatial interpolation methods, such as the thin plate spline (TPS) interpolation (Krypiak‐Gregorczyk et al., 2017), Kriging interpolation (Harsha et al., 2020), and stepwise linear optimal estimation method (Chen et al., 2021) have shown good performance in reflecting the global or local spatial distribution characteristics of TEC. With the rapid development of artificial intelligence (AI), intelligent methods based on machine learning have been introduced into the modeling of TEC and significantly improved the model's accuracy (Han et al., 2022).…”

Section: Introductionmentioning

confidence: 99%

A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction

Wang,

Liu,

Shi

2023

Space Weather

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In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of this method is as follows: (a) Any surface can be uniquely determined by its first and second fundamental quantities; (b) By direct difference approximation, differential equations are transformed into algebraic equations to solve Gauss equations faster. At the same time, taking parts of Europe as an example, the proposed HASR method is used to determine the correlation coefficients and the number of iterations of the model by using the relative root mean square error (RRMSE) as the evaluation criterion. The statistical results show that the TEC predicted by the HASR method is highly consistent with the actual observed values of ionospheric observation stations, and the prediction RRMSE is 9.75%. Compared with the Kriging interpolation with scale factor, the prediction accuracy of the HASR method is improved by 8.5%. We hope this method can provide ideas for the spatial reconstruction of other ionospheric parameters and further promote the realization of complete and accurate space weather forecast.

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Kriging‐based ionospheric TEC, ROTI and amplitude scintillation index (S₄) maps for India

Cited by 13 publications

References 56 publications

Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision

Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision

Investigating the Effects of Ionospheric Scintillation on Multi‐Frequency BDS‐2/BDS‐3 Signals at Low Latitudes

A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction

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