Detection of Arctic Ocean tides using interferometric GNSS-R signals

Semmling, A. M.; Beyerle, G.; Stosius, Ralf; Dick, Galina; Wickert, Jens; Fabra, Fran; Cardellach, Estel; Ribó, S.; Rius, A.; Helm, A.; Yudanov, S.; D’Addio, Salvatore

doi:10.1029/2010gl046005

Cited by 66 publications

(53 citation statements)

References 15 publications

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“…By the same arguments as in (9), the surface integral in (12) vanishes if the incident field only is inserted for the surface fields, keeping in mind that we treat only sources within the volume in this section. The vector incident field used below to calculate fields to insert in (12) is therefore the first term in (12) dotted intop rec evaluated at x (13) where the incident polarizationp inc is the unit-vector direction of E 0 , determined by the currents and charges associated with the transmitter, and A inc is defined on the right side of (13) for use in (14) below.…”

Section: Received Field For a Vector Wavementioning

confidence: 99%

“…In (9), the variation of E y0 due to its dependence on the unit vector in the direction x − x s is assumed negligible over the surface contributing to the integral. When the field at the surface is taken to be just the incident field due to a source within the volume, with no reflected wave (R y = 0), (9) demonstrates that the surface integral vanishes. Therefore, identifying the incident field as in the last line of (9) is consistent with its being the first term in (7) for the wave received anywhere in the volume.…”

Section: The Kirchhoff Approximation To Evaluate the Surface Integralmentioning

confidence: 99%

“…The ocean-scattered electromagnetic waves from Global Navigation Satellite System (GNSS) signals are being explored for their potential to estimate characteristics of the ocean surface and inferred wind vectors, e.g., [1][2][3][4][5][6][7][8][9]. In addition to the scattered power received from GNSS signals, it is plausible that the polarimetric characteristics of the amplitude and phase of the received wave will also carry information about the surface roughness and consequent wind speed [10].…”

Section: Introductionmentioning

confidence: 99%

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Formulating a Vector Wave Expression for Polarimetric GNSS Surface Scattering

Treuhaft¹,

Lowe²,

Cardellach³

2011

PIER B

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Abstract-This paper formulates a simple vector integral expression for electromagnetic waves received after scattering from a surface. The derived expression is an alternative to the Stratton-Chu equation frequently used for polarimetric surface scattering. It is intended for use in polarimetric Global Navigation Satellite System (GNSS) ocean remote sensing, or any type of polarimetric remote sensing from surfaces, when the surface roughness pattern is known from simulation or data. This paper is intended to present a complete accounting of the steps leading to the simpler vector integral expression. It therefore starts with the scalar case, using Maxwell's equations and Green's theorem. It principally treats the case of a transmitter within the integration volume, but discusses how the formalism changes if the transmitter is outside of the integration volume, as with plane waves. It then shows how the scalar expression can be extended to a vector expression for the component of the electric field in an arbitrary receive-polarization direction due to scattering from a rough surface of an incident wave with an arbitrary transmit polarization. It uses the Kirchhoff, or tangent-plane, approximation in which each facet on the ocean is considered to specularly reflect the incoming signal. The derived vector expression is very similar to that for a scalar wave, but it includes all vector properties of the scattering. Equivalence is demonstrated between the Stratton-Chu equation and the derived, simpler expression, which is operationally easier to code than the Stratton-Chu equation in many modeling applications.

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Section: Received Field For a Vector Wavementioning

confidence: 99%

Section: The Kirchhoff Approximation To Evaluate the Surface Integralmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Formulating a Vector Wave Expression for Polarimetric GNSS Surface Scattering

Treuhaft¹,

Lowe²,

Cardellach³

2011

PIER B

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“…Over the last twenty years, this technique has been used to retrieve accurate sea surface heights from various ground-based and airborne platforms using an upward Right-Handed Circular Polarization (RHCP) antenna, a downward Left-Handed Circular Polarization (LHCP) antenna and a specialized receiver [9][10][11][12][13][14]. Space-borne GNSS-R altimetry has been used to retrieve sea surface height (SSH) data with an accuracy of~7.0 m using data from the British TechDemoSat-1 (TDS-1) satellite [15].…”

Section: Introductionmentioning

confidence: 99%

Sea Level Estimation Based on GNSS Dual-Frequency Carrier Phase Linear Combinations and SNR

Wang

Gao

et al. 2018

Remote Sensing

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Abstract:Ground-based GNSS-R (global navigation satellite system reflectometry) can provide the absolute vertical distance from a GNSS antenna to the reflective surface of the ocean in a common height reference frame, given that vertical crustal motion at a GNSS station can be determined using direct GNSS signals. This technique offers the advantage of enabling ground-based sea level measurements to be more accurately determined compared with traditional tide gauges. Sea level changes can be retrieved from multipath effects on GNSS, which is caused by interference of the GNSS L-band microwave signals (directly from satellites) with reflections from the environment that occur before reaching the antenna. Most of the GNSS observation types, such as pseudo-range, carrier-phase and signal-to-noise ratio (SNR), suffer from this multipath effect. In this paper, sea level altimetry determinations are presented for the first time based on geometry-free linear combinations of the carrier phase at low elevation angles from a fixed global positioning system (GPS) station. The precision of the altimetry solutions are similar to those derived from GNSS SNR data. There are different types of observation and reflector height retrieval methods used in the data processing, and to analyze the performance of the different methods, five sea level determination strategies are adopted. The solutions from the five strategies are compared with tide gauge measurements near the GPS station, and the results show that sea level changes determined from GPS SNR and carrier phase combinations for the five strategies show good agreement (correlation coefficient of 0.97-0.98 and root-mean-square error values of <0.2 m).

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“…The time delay can be interpreted in terms of altimetry as the difference in height between the receiver and the surface. Temporal variations of sea (Lowe et al, 2002;Ruffini et al, 2004;Löfgren et al, 2011;Semmling et al, 2011;Rius et al, 2012) and lake levels (Treuhaft et al, 2004;Helm, 2008) were recorded with an accuracy of a few cm using in situ and airborne antennas. Surface roughness can be estimated from the analysis of the delay Doppler maps (DDM) derived from the waveforms of the reflected signals.…”

Section: Introductionmentioning

confidence: 99%

Simulations of direct and reflected wave trajectories for ground-based GNSS-R experiments

et al. 2014

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Abstract. The detection of Global Navigation Satellite System (GNSS) signals that are reflected off the surface, along with the reception of direct GNSS signals, offers a unique opportunity to monitor water level variations over land and ocean. The time delay between the reception of the direct and reflected signals gives access to the altitude of the receiver over the reflecting surface. The field of view of the receiver is highly dependent on both the orbits of the GNSS satellites and the configuration of the study site geometries. A simulator has been developed to determine the location of the reflection points on the surface accurately by modeling the trajectories of GNSS electromagnetic waves that are reflected by the surface of the Earth. Only the geometric problem was considered using a specular reflection assumption. The orbit of the GNSS constellation satellites (mainly GPS, GLONASS and Galileo), and the position of a fixed receiver, are used as inputs. Four different simulation modes are proposed, depending on the choice of the Earth surface model (local plane, osculating sphere or ellipsoid) and the consideration of topography likely to cause masking effects. Angular refraction effects derived from adaptive mapping functions are also taken into account. This simulator was developed to determine where the GNSS-R receivers should be located to monitor a given study area efficiently. In this study, two test sites were considered: the first one at the top of the 65 m Cordouan lighthouse in the Gironde estuary, France, and the second one on the shore of Lake Geneva (50 m above the reflecting surface), at the border between France and Switzerland. This site is hidden by mountains in the south (orthometric altitude up to 2000 m), and overlooking the lake in the north (orthometric altitude of 370 m). For this second test site configuration, reflections occur until 560 m from the receiver. The planimetric (arc length) differences (or altimetric difference as WGS84 ellipsoid height) between the positions of the specular reflection points obtained considering the Earth's surface as an osculating sphere or as an ellipsoid were found to be on average 9 cm (or less than 1 mm) for satellite elevation angles greater than 10 • , and 13.9 cm (or less than 1 mm) for satellite elevation angles between 5 and 10 • . The altimetric and planimetric differences between the plane and sphere approximations are on average below 1.4 cm (or less than 1 mm) for satellite elevation angles greater than 10 • and below 6.2 cm (or 2.4 mm) for satellite elevation angles between 5 and 10 • . These results are the means of the differences obtained during a 24 h simulation with a complete GPS and GLONASS constellation, and thus depend on how the satellite elevation angle is sampled over the day of simulation. The simulations highlight the importance of the digital elevation model (DEM) integration: average planimetric differences (or altimetric) with and without integrating the DEM (with respect to the ellipsoid approximation) were found to...

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Detection of Arctic Ocean tides using interferometric GNSS-R signals

Cited by 66 publications

References 15 publications

Formulating a Vector Wave Expression for Polarimetric GNSS Surface Scattering

Formulating a Vector Wave Expression for Polarimetric GNSS Surface Scattering

Sea Level Estimation Based on GNSS Dual-Frequency Carrier Phase Linear Combinations and SNR

Simulations of direct and reflected wave trajectories for ground-based GNSS-R experiments

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