Sensing the ionosphere with the Spire radio occultation constellation

Angling, Matthew; Nogués-Correig, O.; Nguyen, Vien; Vetra-Carvalho, Sanita; Bocquet, François-Xavier; Nordstrom, Karl F.; Melville, Stacey E.; Savastano, Giorgio; Mohanty, Shradha; Masters, Dallas

doi:10.1051/swsc/2021040

Cited by 31 publications

(18 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further steps toward collaborative imaging of the ionosphere will likely involve ultraviolet spectrographs with the capability of sensing the plasma density, such as GOLD [70,71], and spacecraft-to-spacecraft Radio Occultation (RO) networks, such as SPIRE [72] and FORMOSAT-7/COSMIC-2 [73]. Although practical considerations of the high expense of RT telemetry downlink delay the availability of RO measurements by as much as 2 h, new machine learning capabilities are emerging for ionospheric weather forecasting [74] that may satisfy the accuracy requirements of most applications.…”

Section: Summary and Future Workmentioning

confidence: 99%

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

et al. 2022

View full text Add to dashboard Cite

Prompt and accurate imaging of the ionosphere is essential to space weather services, given a broad spectrum of applications that rely on ionospherically propagating radio signals. As the 3D spatial extent of the ionosphere is vast and covered only fragmentarily, data fusion is a strong candidate for solving imaging tasks. Data fusion has been used to blend models and observations for the integrated and consistent views of geosystems. In space weather scenarios, low latency of the sensor data availability is one of the strongest requirements that limits the selection of potential datasets for fusion. Since remote plasma sensing instrumentation for ionospheric weather is complex, scarce, and prone to unavoidable data noise, conventional 3D-var assimilative schemas are not optimal. We describe a novel substantially 4D data fusion service based on near-real-time data feeds from Global Ionosphere Radio Observatory (GIRO) and Global Navigation Satellite System (GNSS) called GAMBIT (Global Assimilative Model of the Bottomside Ionosphere with Topside estimate). GAMBIT operates with a few-minute latency, and it releases, among other data products, the anomaly maps of the effective slab thickness (EST) obtained by fusing GIRO and GNSS data. The anomaly EST mapping aids understanding of the vertical plasma restructuring during disturbed conditions.

show abstract

Section: Summary and Future Workmentioning

confidence: 99%

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Figure 1 shows an example of the coverage of Spire GNSS-RO profiles collected on 12 May 2020. A description of the measurement system can be found (Angling et al, 2021).…”

Section: Data Collection Systemmentioning

confidence: 99%

“…Space-based GNSS-RO sTEC measurements are collected in an atmospheric limb sounding geometry where the GNSS receiver (Rx) is on an LEO satellite (Angling et al, 2021). As the LEO satellite moves in its orbit, the GNSS satellite (Tx) is seen to rise above or set below the horizon.…”

Section: Data Collection Systemmentioning

confidence: 99%

Semi-supervised classification of lower-ionospheric perturbations using GNSS radio occultation observations from Spire Global’s Cubesat Constellation

Savastano¹,

Nordstrom²,

Angling³

2022

J. Space Weather Space Clim.

Self Cite

View full text Add to dashboard Cite

In this study, we present a new methodology to automatically classify perturbations in the lower ionosphere using GNSS radio occultation (RO) observations collected using Spire’s constellation of CubeSats. This methodology combines signal processing techniques with semi-supervised machine learning by applying spectral clustering in a metric space of wavelet spectra. A “bottom-up” algorithm was applied to extract E layer information directly from Spire’s high-rate (50 Hz) GNSS-RO profiles by subtracting the effect of the F layers. This processing algorithm has been implemented in our ground segment to operationally produce high rate sTEC profiles with a vertical resolution of better than 100 m. The key idea behind the semi-supervised classification is to produce a database of labeled clusters that can be used to classify new unlabeled data by determining which cluster it belongs to. A dataset of more than 12000 GNSS-RO profiles collected in 2019 containing sTEC perturbations is used to find the initial clusters. This dataset is used as a representation of the climatology of ionospheric perturbations, such as MSTIDs and sporadic Es. The wavelet power spectrum (WPS) is computed for these profiles, and a metric space is defined using the Earth mover's distance (EMD) between the WPS. A self-tuning spectral clustering algorithm is used to cluster the profiles in this metric space. These clusters are used as a reference database of perturbations to classify new sTEC profiles by finding the cluster of the closest profile of the clustered dataset in the EMD metric space. This new methodology is used to construct an automated system to monitor ionospheric perturbations on a global scale.

show abstract

“…The most well‐known companies include the Spire, the GeoOptics, and the PlanetIQ. Spire (https://spire.com/) is a pioneer company which aims to collect massive satellite observing data to support the aviation, weather, maritime, and earth intelligence applications (Angling et al., 2021). They have constructed a constellation of 110+ multi‐payload LEO nanosatellites and kept updating.…”

Section: Introductionmentioning

confidence: 99%

The Ionospheric Exploration Based on TJU#01 Meteorological Microsatellite Mission: Initial Results

Wu,

Guo,

et al. 2023

Radio Science

View full text Add to dashboard Cite

The global navigation satellite system radio occultation technique is achieving increasing significance and extensive promotion in the remote sensing of near‐earth atmosphere, climate, and ionosphere in recent three decades. Nowadays, many communities become interested in developing commercial mode in occultation measurement by launching massive nano‐ or cube satellite constellations at low costs. The TJU#01 is the first meteorological satellite of Tianjin Yunyao Aerospace Technology Co., Ltd. which was successfully launched into space on 7 December 2021. The occultation antenna onboard the satellite is able to probe both the ionosphere and atmosphere at multi‐frequencies including GPS, GLONASS, and BEIDOU systems. The microsatellite applies the same occultation antenna to receive both the atmospheric and ionospheric occultations at 100 and 1 Hz respectively. 100 Hz narrow band power and wide band power data are downloaded to the ground to generate high‐rate signal‐to‐noise ratio (SNR) series and applied to ionospheric scintillation exploration. In this paper, the primary parameters of the satellite and occultation antenna are introduced, as well as the ionospheric data processing methodologies. The initial ionospheric products of TJU#01 are evaluated after one‐month in orbit. The TJU#01 results have a good agreement with the co‐located ground ionosonde data and COSMIC‐2 observations. The new satellite and its follow‐on missions have great capabilities and potentials in the ionospheric and space weather researches.

show abstract

Sensing the ionosphere with the Spire radio occultation constellation

Cited by 31 publications

References 51 publications

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

Semi-supervised classification of lower-ionospheric perturbations using GNSS radio occultation observations from Spire Global’s Cubesat Constellation

The Ionospheric Exploration Based on TJU#01 Meteorological Microsatellite Mission: Initial Results

Contact Info

Product

Resources

About