Distributed sensing of ionospheric irregularities with a GNSS receiver array

Su, Yang; Datta‐Barua, Seebany; Bust, G. S.; Deshpande, K.

doi:10.1002/2017rs006331

Cited by 13 publications

(27 citation statements)

References 17 publications

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“…It is worth mentioning that the work presented in Wang and Morton () and this paper are in parallel with Su et al (). Both studies address the ionospheric drift velocity remote sensing problem using receiver arrays at a similar location.…”

Section: Introductionsupporting

confidence: 73%

New Results on Ionospheric Irregularity Drift Velocity Estimation Using Multi‐GNSS Spaced‐Receiver Array During High‐Latitude Phase Scintillation

2018

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The spaced‐receiver technique using Global Navigation Satellite Systems (GNSS) receivers offers an inexpensive approach for estimating ionospheric irregularity velocity during ionospheric scintillations. Our previous work has demonstrated that correlative studies of the GNSS carrier phase variations can be used to derive irregularity drift velocity at high latitudes. This study expanded upon our previous projects by incorporating Global Navigation Satellite System (GLONASS) signals, investigation on ionospheric irregularity height assumption, and all‐sky imager measurements into the methodology. A case study is presented based on Global Positioning System, Galileo, and GLONASS measurements during a geomagnetic storm event on 20 December 2015, obtained from a closely spaced receiver array at Poker Flat Research Range near Fairbanks, Alaska. The GNSS‐estimated irregularity drift velocities are in general agreement with the measurements from the Poker Flat Incoherent Scatter Radar and the Poker Flat all‐sky imager. The study also shows that the irregularity altitude assumption will not lead to significant variations in the irregularity drift velocity estimates, especially for satellites with relatively high elevations. The techniques presented in this paper demonstrate that GNSS receiver arrays can be used as powerful means to monitor the ionospheric plasma dynamics during space weather events.

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Section: Introductionsupporting

confidence: 73%

New Results on Ionospheric Irregularity Drift Velocity Estimation Using Multi‐GNSS Spaced‐Receiver Array During High‐Latitude Phase Scintillation

2018

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“…PFISR measurements on 8 December 2013 of (a) electron density, (b) electron temperature, and (c) ion temperature over altitude and time. From 03:43 to 04:17 UT an L1 phase scintillation event was identified by Su, Datta‐Barua, et al (). PFISR measurements on 7 October 2015 of (d) electron density, (e) electron temperature, and (f) ion temperature over altitude and time.…”

Section: Methodsmentioning

confidence: 99%

“…We use two case studies in the literature (Semeter et al, ; Su, Datta‐Barua, et al, ) to help determine which PFISR data parameter, density, or ion or electron temperature, is a reasonable single indicator of the layer correlated with the GPS scintillations. The first case study from the literature is an F‐region scintillation on 8 December 2013 (Datta‐Barua et al, ; Su, Datta‐Barua, et al, ). According to those studies, the peak electron densities and the highest electron temperature were observed to occur in the F‐region altitudes at the same time during which the scintillation had occurred, from about 03:43 to 04:17 UT.…”

Section: Methodsmentioning

confidence: 99%

“…While GNSS scintillations have been shown to be correlated with the locations of visible auroral activity (Kintner et al, ), a number of them have been apparently F layer aurorae. Prior work (Su, ) examined a number of scintillations, at least one of which was attributed to the F layer (Datta‐Barua et al, ; Su, Datta‐Barua, et al, ). More recently, individual case studies (Loucks et al, ; Semeter et al, ) showed the possibility that E layer irregularities, particularly related to auroral activity, were correlated with GPS‐effective scintillations.…”

Section: Introductionmentioning

confidence: 99%

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Automated Ionospheric Scattering Layer Hypothesis Generation for Detected and Classified Auroral Global Positioning System Scintillation Events

Sreenivash

Datta‐Barua

2020

Radio Science

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We describe a method to detect and classify global positioning system (GPS) scintillation, and then hypothesize a possible ionospheric layer scattering the signal. The objective is to routinely identify events of interest to investigate in detail in future work. Scintillation types include amplitude, phase, or both amplitude and phase. A scintillation event is one for which a scintillation index remains above a threshold across a majority of closely spaced receivers viewing a single satellite. Events are categorized by signal frequency and scintillation type. An event is then hypothesized to be due to the E or F layer using an independent data source. Data from the scintillation auroral GPS array located in Poker Flat Research Range, Alaska, are used to analyze L1 and L2C frequencies in 2014 and 2015. The irregularity layer associated with each scintillation event is hypothesized to be due to the activity in the E layer of the ionosphere (below 150 km) or in the F layer (above 195 km) using collocated Poker Flat Incoherent Scatter Radar electron density measurements. Events in a transition layer (150-195 km) and inconclusive results are also recorded. We find that nearly all of the over 4,000 events are phase scintillations. The majority of the events are hypothesized to occur when the peak density is at E-layer altitudes. This indicates that E-layer-related scintillation may be quite common at auroral latitudes and that GPS receivers are sensitive to the irregularities occurring both there and at F layer altitudes.Plain Language Summary As global positioning system (GPS) signals pass through Earth's atmosphere, they may "twinkle" when received at the ground due to variations in the number of charged particles present in the ionized layer of the Earth's atmosphere, the ionosphere. The twinkling or rapid fluctuation in the GPS signals is called ionospheric scintillation. We develop a way, using data from GPS receivers and a nearby radar, to detect and classify scintillations measured in Alaska in 2014 and 2015, and then make an educated guess about whether they are in the upper or lower layer of the ionosphere. This method will be useful for handling large data sets of scintillation, which are now becoming more common. We find that, even though most of the ionosphere's charged particles are usually above 195 km height, GPS is sensitive to scintillations at high latitudes due to variations in a lower layer below 150 km, and these happen a majority of the time.

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“…Because of their compact, low cost, and distributive nature, GPS receivers became increasingly popular in this research area (Basu et al, ; Kil et al, , ; Kintner et al, ). With the modernization of Global Navigation Satellite System (GNSS), high‐rate multi‐GNSS carrier phase signals have been utilized in high‐latitude regions (Su et al, ; Wang et al, ; Wang & Morton, , ). The gist of the technique is to find the time delay between receiver measurements through cross correlation when similar diffraction pattern is observed on different receivers.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Correlation Model for the Spaced‐Receiver Technique

Wang

Morton

2019

Radio Science

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A Global Navigation Satellite System (GNSS) spaced‐receiver technique estimates ionospheric irregularity drift velocity by correlating the received GNSS signals across a closely spaced receiver array during ionospheric scintillations. This paper focuses on the correlation models accounting for the topology of the received diffraction pattern. Space‐time correlation schematics are developed to analyze and compare several prevalent models, including the classic isotropy model, the front velocity model, and the anisotropy model. Based on the merits and drawbacks of each model, a hybrid correlation model is proposed, integrating the front velocity model and the anisotropy model. To validate the hybrid model, the corresponding drift velocity estimates are cross compared with the measurements from a colocated all‐sky imager and incoherent scatter radar. A case study was conducted for a geomagnetic storm event on 20 December 2015. Favorable agreement was found in terms of direction and magnitude of the drift motion, orientation of the irregularity, temporal and spatial features of the irregularity, and the statistical behavior of the drift velocity estimates. In addition, the root‐mean‐square velocity magnitude and orientation against the incoherent scatter radar measurements demonstrate the superior performance of the hybrid model.

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Distributed sensing of ionospheric irregularities with a GNSS receiver array

Cited by 13 publications

References 17 publications

New Results on Ionospheric Irregularity Drift Velocity Estimation Using Multi‐GNSS Spaced‐Receiver Array During High‐Latitude Phase Scintillation

New Results on Ionospheric Irregularity Drift Velocity Estimation Using Multi‐GNSS Spaced‐Receiver Array During High‐Latitude Phase Scintillation

Automated Ionospheric Scattering Layer Hypothesis Generation for Detected and Classified Auroral Global Positioning System Scintillation Events

A Hybrid Correlation Model for the Spaced‐Receiver Technique

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