GNSS-Based Model-Free Sea Surface Height Estimation in Unknown Sea State Scenarios

Yu, Kegen; Rizos, Chris; Dempster, Andrew G.

doi:10.1109/jstars.2013.2293371

Cited by 29 publications

(15 citation statements)

References 16 publications

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“…t R and t D are determined based on the peaks of their corresponding waveforms. The height of the surface under investigation can be determined from an obtained path delay using the method either described in [99,100] or [101]. The estimated precision is about 1 m with a spatial resolution of 3.8 km.…”

Section: Waveform-basedmentioning

confidence: 99%

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: Waveform-basedmentioning

confidence: 99%

Sea Ice Remote Sensing Using GNSS-R: A Review

Yan

Huang

2019

Remote Sensing

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“…To convert the path delay to the height of the reflecting surface with respect to the WGS-84 ellipsoid surface, the two-loop iterative method proposed in [22] is employed. Other approaches are described in [6] and [23].…”

Section: B Data Processingmentioning

confidence: 99%

Single-Pass Sub-Meter Space-Based GNSS-R Ice Altimetry: Results From TDS-1

Benson

Rizos

et al. 2017

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Space-based Global Navigation Satellite System Reflectometry (GNSS-R) altimetry remains an open challenge. This paper reports on space-based GNSS-R altimetry using 40-s period of intermediate frequency recording from the TechDemoSat-1 mission. This recording is unique because one GPS signal is reflected from ice. The waveforms that are used to determine path delay are generated by 1 ms coherent integration. Pseudoranges are smoothed every 0.5 s by linear models before calculating the path delay. Altimetric results are compared to DTU10 mean sea surface heights, with good agreement being obtained. The RMS difference of 4.4 m is much smaller than reported in the current literature. Very good altimetric precision of better than 1 m (0.96 m) is achieved with a spatial resolution of 3.8 km. This result validates the potential of space-based GNSS-R altimetry. Index Terms-Altimetry, global navigation satellite system reflectometry (GNSS-R), space-based GNSS-R, waveform.

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“…Rius et al [38] investigated the scatterometric and specular delay observables and considered various sources of uncertainty including observation statistics and model parameterisation or calibration error. Methodology studies include an investigation of model-free retrieval of sea surface height using a power ratio method combined with cost function optimisation when the sea surface is rather rough [39]. A semi-codeless processing approach [40] showed how to determine the phase sign variation of encrypted P-code GNSS signals and combine it with the CA signal stream to enhance signal to noise ratio in comparison with that achieved by the interferometric method.…”

Section: Ocean Observationmentioning

confidence: 99%

“…Useful reviews of ground-based and airborne GNSS-R campaigns, geophysical models and signal processing techniques for a variety of oceanographic applications are available [2,44]. Campaigns performed over ocean surfaces have spanned locations in the North Sea, the Baltic Sea, the Mediterranean Sea and the Atlantic Ocean [44], and the Tasman Sea in the western South Pacific [39]. Newly developed GNSS-R signal processing techniques, exploiting favourable sampling geometries or instrument refinements, can now be used to extract such factors as significant wave height and roughness field directionality [38,54] or to relate ocean roughness to surface brightness temperature measured at microwave frequencies [57,58].…”

Section: Ocean Observationmentioning

confidence: 99%

An overview of GNSS remote sensing

Rizos

Burrage

et al. 2014

EURASIP J. Adv. Signal Process.

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The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing -the atmosphere, oceans or Earth surface -was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters. Review

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GNSS-Based Model-Free Sea Surface Height Estimation in Unknown Sea State Scenarios

Cited by 29 publications

References 16 publications

Sea Ice Remote Sensing Using GNSS-R: A Review

Sea Ice Remote Sensing Using GNSS-R: A Review

Single-Pass Sub-Meter Space-Based GNSS-R Ice Altimetry: Results From TDS-1

An overview of GNSS remote sensing

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