On estimating the phase scintillation index using TEC provided by ISM and IGS professional GNSS receivers and machine learning

Imam, Rayan; Alfonsi, Lucilla; Spogli, Luca; Cesaroni, Claudio; Dovis, Fabio

doi:10.1016/j.asr.2023.07.039

Cited by 3 publications

(1 citation statement)

References 50 publications

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“…The S 4c shows a high correlation with S 4 . However, compared with ISMRs which employ resilient tracking loops, low-phase noise oscillators, and stable clocks with advanced signal processing techniques, geodetic receivers are more susceptible to noise and multipath interference (Imam et al, 2023). Using S 4c derived from geodetic receivers for scintillation detection might suffer from a significant risk of missed detection and false alarms.…”

Section: Introductionmentioning

confidence: 99%

Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree

Li,

Jiang,

et al. 2024

Satell Navig

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The amplitude scintillation detection is typically achieved by using the scintillation index generated by dedicated and costly ionospheric scintillation monitoring receivers (ISMRs). Considering the large volume of common Global Navigation Satellite System (GNSS) receivers, this paper presents a strategy to accurately identify the ionospheric amplitude scintillation events utilizing the measurements collected with geodetic GNSS receivers. The proposed detection method relies on a pre-trained machine learning decision tree algorithm, leveraging the scintillation index computed from the carrier-to-noise data and elevation angles collected at 1-Hz. The experimental results using real data demonstrate a 99% accuracy in scintillation detection can be achieved. By combining advanced machine learning techniques with geodetic GNSS receivers, this approach is feasible to effectively detect ionospheric scintillation using non-scintillation GNSS receivers.

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Section: Introductionmentioning

confidence: 99%

Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree

Li,

Jiang,

et al. 2024

Satell Navig

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Natural-hazard monitoring with global navigation satellite systems (GNSS)

Hohensinn,

Aichinger-Rosenberger,

Wareyka-Glaner

et al. 2024

Advances in Geophysics

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Geomagnetic storm effect on equatorial ionosphere over Sri Lanka through total electron content observations from continuously operating reference stations network during Mar–Apr 2022

Thiruvarangan,

Rajavarathan,

Panda

et al. 2024

Journal of Applied Geodesy

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The technological advancements in the current era have highlighted the increasing significance of satellite-based positioning, navigation, and timing services in a wide range of dynamic and critical applications. This has led to significant efforts towards enhancing the performance of global navigation satellite systems (GNSS) operating under challenging ionospheric conditions. The Sri Lankan ionosphere region is a focal point of equatorial aeronomy scientists, being situated in the southernmost landmass of the Indian longitude sector within the vicinity of the magnetic equator where a combination of electric, wind, and temperature dynamics exerts a substantial influence on the ionosphere but was relatively unexplored in the past. In the present work, we employed a Kriging interpolation technique on the total electron content (TEC) variables from ten GNSS receivers operating under the Continuously Operating Reference Stations (CORS) network in Sri Lanka first ever of its kind to deliver two-dimensional regional ionospheric TEC maps at hourly intervals, both during quiet and disturbed ionospheric conditions in the equinoctial March and April months of 2022. The latitudinal variation patterns are discernable from the hourly TEC maps. Furthermore, a comparative analysis of the performance of GNSS-derived TEC with that of the routinely published Global Ionospheric Maps (GIMs) confirms overestimation characteristics of the latter irrespective of the local time of observation. The generated regional ionospheric maps are fairly responsive to the onset of the storm and the recovery phase thereafter. The extent of nighttime ionospheric irregularity is also probed through the rate of TEC index (ROTI) variations, demonstrating that the irregularities were insignificant during the selected storm event.

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On estimating the phase scintillation index using TEC provided by ISM and IGS professional GNSS receivers and machine learning

Cited by 3 publications

References 50 publications

Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree

Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree

Natural-hazard monitoring with global navigation satellite systems (GNSS)

Geomagnetic storm effect on equatorial ionosphere over Sri Lanka through total electron content observations from continuously operating reference stations network during Mar–Apr 2022

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