Coastal Sea Ice Detection Using Ground-Based GNSS-R

Strandberg, Joakim; Hobiger, Thomas; Haas, Rüdiger

doi:10.1109/lgrs.2017.2722041

Cited by 31 publications

(27 citation statements)

References 18 publications

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“…Although the coverage area by a ground-based receiver is quite limited compared to spaceborne and airborne instruments, GNSS sites can provide long-term observations for specific regions of interests. The sea ice information obtained from coastal GNSS-R can be regarded as ground-truth for validating spaceborne and airborne sensors [61]. With increasing ground GNSS stations, more intensive coverage and more data will be accessible at a regional scale [42], it is thus possible to further develop sea ice sensing schemes in the future.…”

Section: Discussionmentioning

confidence: 99%

“…Signal-to-noise ratio (SNR) data of received reflected GNSS signals were collected at the Onsala Space Observatory, Sweden in [61,102]. The high-frequency part of the SNR data, referred to as δSNR, can be modeled as…”

Section: Ground-based Operationsmentioning

confidence: 99%

“…C 1 , C 2 , m, and γ can be determined through nonlinear least squares fitting using Equation (31). It was found in [61] that low values of γ were coincident with the presence of ice, and thus γ can be used for ice detection.…”

Section: Ground-based Operationsmentioning

confidence: 99%

“…Sea ice remote sensing using GNSS-R was first demonstrated by [58] with an airborne GPS Rx. Since then, several ground-based and airborne experiments have been accomplished with promising results [56,57,[59][60][61]. The first spaceborne GNSS-R measurement was carried out during the UK Disaster Monitoring Constellation (UK-DMC) mission in 2004 showing its capability of sea ice remote sensing.…”

Section: Introductionmentioning

confidence: 99%

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Sea Ice Remote Sensing Using GNSS-R: A Review

Yan

Huang

2019

Remote Sensing

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Knowledge of sea ice is critical for offshore oil and gas exploration, global shipping industries, and climate change studies. During recent decades, Global Navigation Satellite System-Reflectometry (GNSS-R) has evolved as an efficient tool for sea ice remote sensing. In particular, thanks to the availability of the TechDemoSat-1 (TDS-1) data over high-latitude regions, remote sensing of sea ice based on spaceborne GNSS-R has been rapidly growing. The goal of this paper is to provide a review of the state-of-the-art methods for sea ice remote sensing offered by the GNSS-R technique. In this review, the fundamentals of these applications are described, and their performances are evaluated. Specifically, recent progress in sea ice sensing using TDS-1 data is highlighted including sea ice detection, sea ice concentration estimation, sea ice type classification, sea ice thickness retrieval, and sea ice altimetry. In addition, studies of sea ice sensing using airborne and ground-based data are also noted. Lastly, applications based on various platforms along with remaining challenges are summarized and possible future trends are explored. In this review, concepts, research methods, and experimental techniques of GNSS-R-based sea ice sensing are delivered, and this can benefit the scientific community by providing insights into this topic to further advance this field or transfer the relevant knowledge and practice to other studies.

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Section: Discussionmentioning

confidence: 99%

Section: Ground-based Operationsmentioning

confidence: 99%

Section: Ground-based Operationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sea Ice Remote Sensing Using GNSS-R: A Review

Yan

Huang

2019

Remote Sensing

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“…The amplitude, phase, and damping parameters are all affected by various properties of the surroundings. In an earlier paper by Strandberg et al (2017), it was shown that these effects are susceptible to changes in the antenna environment and that especially the damping is useful to determine the presence of ice on the water surface and that least-squares inversion is capable of retrieving the information. In Fig.…”

Section: Retrieving Properties Of the Reflecting Surfacementioning

confidence: 99%

Real-time sea-level monitoring using Kalman filtering of GNSS-R data

2019

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Current GNSS-R (GNSS reflectometry) techniques for sea surface measurements require data collection over longer periods, limiting their usability for real-time applications. In this work, we present a new, alternative GNSS-R approach based on the unscented Kalman filter and the so-called inverse modeling approach. The new method makes use of a mathematical description that relates SNR (signal-to-noise ratio) variations to multipath effects and uses a B-spline formalism to obtain time series of reflector height. The presented algorithm can provide results in real time with a precision that is significantly better than spectral inversion methods and almost comparable to results from inverse modeling in post-processing mode. To verify the performance, the method has been tested at station GTGU at the Onsala Space Observatory, Sweden, and at the station SPBY in Spring Bay, Australia. The RMS (root mean square) error with respect to nearby tide gauge data was found to be 2.0 cm at GTGU and 4.8 cm at SPBY when evaluating the output corresponding to real-time analysis. The method can also be applied in post-processing, resulting in RMS errors of 1.5 cm and 3.3 cm for GTGU and SPBY, respectively. Finally, based on SNR data from GTGU, it is also shown that the Kalman filter approach is able to detect the presence of sea ice with a higher temporal resolution than the previous methods and traditional remote sensing techniques which monitor ice in coastal regions.

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Software tools for GNSS interferometric reflectometry (GNSS-IR)

2018

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GNSS-R interferometric reflectometry (also known as GNSS-IR, or GPS-IR for GPS signals) is a technique that uses data from geodetic-quality GNSS instruments for sensing the near-field environment. In contrast to positioning, atmospheric, and timing applications of GNSS, GNSS-IR uses the signal-to-noise ratio (SNR) data. Software is provided to translate GNSS files, map GNSS-IR reflection zones, calculate GNSS-IR Nyquist frequencies, and estimate changes in the height of a reflecting surface from GNSS SNR data.

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Coastal Sea Ice Detection Using Ground-Based GNSS-R

Cited by 31 publications

References 18 publications

Sea Ice Remote Sensing Using GNSS-R: A Review

Sea Ice Remote Sensing Using GNSS-R: A Review

Real-time sea-level monitoring using Kalman filtering of GNSS-R data

Software tools for GNSS interferometric reflectometry (GNSS-IR)

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