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GOLD_RTR MINING
 
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GNSS-R Measurement Concept

The Global Navigation Satellite System Reflectometry (GNSS-R) aims to retrieve information about the Earth surface by analyzing the signals emitted by GNSS transmitters (such as GPS, GLONASS, GALILEO, future COMPASS...), and captured by an elevated platform after the signal has rebounded off of the Oceans, Land, Lakes, or Ice and Snow. The system has the characteristics of a bi-static radar and scatterometre, at L-band.

The observables of the GNSS and GNSS-R in particular, are the waveforms, the cross-correlation between the signals and replicas (models) of them. Only replicas modelled appropriately (with the GNSS Pseudo-Random-Noise - PRN, the range and frequency corresponding to the incoming signal) will generate waveforms above the noise. Therefore, tunning the replicas to the right parameters permits to know the range and frequency -changes in the range- associated to a given satellite-receiver radio-link.

An alternative approach to obtain GNSS-R waveforms is by cross-correlating the reflected signals against the line-of-sight (direct radio-link) ones. This technique is the one suggested for the ESA PARIS In Orbit Demonstrator mission (PARIS-IOD) [Martín-Neira, 2011], and it has the advantage of using the entire bandwidth of the transmitted signal, including the encrypted codes. Our experiments have shown that this technique provides altimetric estimates of at least twice precision than the clean-replica (conventional) approach. [Cardellach et al., 2013].

By comparing the ray-path lengths of the reflected and direct radio-links, the vertical distance between the receiving platform and the surface level can be measured. This is the altimetric application. On the other hand, when the distortion of the reflected signal is analyzed, some geophysical parameters that characterize the reflecting surface can be estimated, such as it roughness and dielectric properties. The roughness essentially acts spreading the signal through the glistening zone, reducing the peak power of the reflected waveform and adding contributions at longer delays. These longer delays are the result of signal ray-paths that have been reflected in areas of glistening zone farther away from the specular - the link transmitter-specular-receiver has, by definition, the shortest ray-path (see Figure 1).

Furthermore, generating a waveform by cross-correlating signal and replica during an integration time Ti, filters out any signal arriving with frequencies beyond +- 1/Ti Hz from the central one. Because different surface patches induce different Doppler shifts, only certain areas of the glistening zone will contribute to the cross-correlation. This allows to define Doppler stripes on the surface (areas from which the reflected signal will have the same Doppler shift +- 1/Ti). When the reflected signal is correlated along the central frequency solely, it is called Delay Map (DM). Complementary, the correlation can be repeated for different frequencies, mapping different Doppler stripes. The latter measurement is called Delay-Doppler-Map (DDM).

A review on the large diversity of applications and techniques that potentially can be applied in this GOLD-RTR data set are compiled in Cardellach et al., 2011. A summary is presented in Tables 1 to 4. The techniques are identified by a code, used in the paper to assign different potential applications/methods to different campaigns. The table also informs about the type of data required to proceed with each technique: the first part of the data-code might be either C- or P-, standing for complex or power (raw or integrated data respectively); the second part might be either DM or DDM, for Delay-Map or Delay-Doppler-Maps. Finally, Table 5 lists some of the models involved in GNSS reflectometry.



Figure 1: GNSS-R measurement concept (left): a GNSS satellite transmit L-band signals, that can be received directly by the elevated receiving platform, and also after the signal has rebounded off of the Earth surface. If the surface is smooth, the reflection will be specular (shortest reflected ray-path), otherwise, the signal scatters across a wide area called -glistening area-. (right): if the glistening area is wide enough, their reflections off patches far away from the specular arrive at the receiver with delays with respect to the specular. The surface-points corresponding to ray-paths of equal delay are called iso-range annuli. Similarly, different areas within the glistening will scatter the signal with different Doppler shift than the specular. This defines Doppler stripes. Roughly speaking, a Delay-Map maps the power distribution across the range annuli, whereas a Delay-Doppler-Map also maps the distribution of reflected power across Doppler stripes.

Table 1: List of the GNSS-R altimetric techniques identified in the literature as suitable to be applied in the released data set.
Code: Technique: Bibliography: Data:
GROUP-ALTIMETRY
AG.P Peak-Delay: altimetric range as peak-to-peak delay. In our data set, this is obtained by: NominalDelay (reflected) + WavMaxDelay (reflected) - WavMaxDelay (direct) Martin-Neira et al.,2001 P-DM
AG.R Retracking: Techniques based on fitting a theoretical model to the data. The best-fit model indicates the delay where the specular point lies Lowe et al., 2002,Ruffini et al., 2004 P-DM
AG.D Peak-Derivative: The derivative of the waveform has a maximum at the delay corresponding to the specular point. In our data set, this is obtained with NominalDelay (reflected) + WavDerDelay (reflected) - WavMaxDelay (direct) Hajj and Zuffada, 2003, Rius et al.,2010 P-DM
PHASE-ALTIMETRY
AP.I Interferometric-beats: at low altitude or very grazing observations the delay between the reflected and direct signals is short and their correlation functions overlap, producing interference-beats. These beats are oscillations of the amplitude and phase of the sum of the two signals, and they occur at the frequency 1/\lambda d(r_r-r_d)/dt Cardellach et al., 2004, Helm et al, 2004 RHCP (low altitude or elevation) C-DM
AP.5P 5-Parameter DM Fit: A more robust fit using the whole complex RHCP (direct+reflected) waveform, to extract five parameters, among them the altimetric range Treuhaft et al., 2001 RHCP (low altitude or elevation angle) C-DM
AP.SC Separate Up/Down Channels: The phase between the direct and reflected links is obtained from separate channels, no need of overlap between direct and reflected waveforms, but need to store direct waveforms Fabra et al., 2011 coherent reflected C-DM and direct C-DM



Table 2: List of the GNSS-R Ocean-applications and techniques identified in the literature as suitable to be applied in the released data set.
Code: Technique: Bibliography: Data:
OCEAN ROUGHNESS
OR.DM DM-fit: After re-normalizing and re-aligning the delay-waveform, the best fit againts a theoretical model gives the best estimate for the geophysical and instrumental-correction parameters. Depending on the model used for the fit, the geophysical parameters can be 10-meter altitude wind speed, or sea surface slopes' variance (mean square slopes-MSS). Garrison et al., 2002, Cardellach et al., 2003, Komjathy et al., 2004 P-DM
OR.MDM Multiple-satellite DM-fit: When the same inversion approach is conducted on several simultaneous satellite reflection observations, the anisotropy (wind direction or directional roughness) can be extracted Komjathy et al., 2004 P-DM simultaneous PRNs
OR.DDM DDM-fit: The fit is performed on delay-Doppler waveforms. In this way, anisotropic information can be obtained from a single satellite observation Germain et al., 2004 P-DDM
OR.TE Trailing-edge: The fit is performed on the slope of the trailing edge, given in dB Garrison et al., 2002 P-DM
OR.SD Scatterometric-delay: For a given geometry, the delay between the range of the specular point and the range of the peak of the reflected delay-waveform MaxWavDelay-MaxDerDelay is nearly linear with MSS Nogues-Correig et al., 2007, Rius et al., 2010 P-DM
OR.AV DDM Area/Volume: Simulation work indicates that the volume and the area of the delay-Doppler maps are related to the changes in the contribution to the brightness temperature of the ocean induced by the roughness Marchan et al., 2007 P-DDM
OR.PDF Discrete-PDF: When the bi-static radar equation for GNSS signals is re-organized in a series of terms, each depending on the surface's slope, the system is linear with the Probability Density Function (PDF) of the slopes. Discrete values of the PDF(s) are therefore obtained. This retrieval does not require an analitical model for the PDF (no particular statistics assumed). In particular, when the technique is applied on delay-Doppler-maps, is it possible to obtain the directional roughness, together with other non-Gaussian features of the PDF (such as up/down-wind separation) Cardellach and Rius, 2008 P-DM (isotropic) P-DDM (anisotropic and assymetric)
OR.CT Coherence-time: When the specular component of the scattering is significative (very low altitude observations, very slant geometries, or relatively calm waters), the coherence-time of the interferometric complex field depends on the sea state. It is then possible to develope the algorithms to retrieve significan wave height Soulat et al., 2004 Direct and Reflected C-DM low altitude and/or calm waters
OCEAN PERMITTIVITY
OP.PR Polarimetric-ratio: Ratio between co- and cross-polar componentes - Reflected RHCP and LHCP P-DM
OP.POPI POPI: difference between the carrier-phase of the complex co- and cross-polarized components of the reflected field (RHCP and LHCP respectively) Cardellach et al., 2006 Reflected RHCP and LHCP C-DM


Table 3: List of the GNSS-R land-applications and techniques identified in the literature as suitable to be applied in the released data set.
Code: Technique: Bibliography: Data:
LAND
L.SMC Soil-moisture cross-polar: LHCP SNR is the observable used to extract the surface reflectivity. It can be normalized by the direct power level or even calibrated with observations over smooth water bodies Masters et al., 2004, Manandhar et al., 2006, Katzberg et al., 2005, Cardellach et al., 2009 P-DM and direct P-DM if calibration wanted
L.SMP Soil-moisture polarimetric-ratio: Method based on the assumption that the received signal power is proportional to the product of two factors: a polarization sensitive factor dependent on the soil dielectric properties and a polarization insensitive factor that depends on the surface roughness. Therefore, the ratio of the two orthogonal polarizations excludes the roughness term and retains the dielectric effects. The same references note that real data did not support this hypothesis. Some of the assumptions might be too crude, and better modelling is required Zavorotny and Voronovich 2000, Zavorotny et al., 2003 reflected RHCP and LHCP P-DM
L.OI Object-identification: A combination of computing the GNSS-R derived total reflectivity together with the carrier-phase positioning of both up- and down-looking antennas Lie-Chung et al., 2009 RHCP and LHCP C-DM


Table 4: List of the GNSS-R Ice and Snow applications and techniques identified in the literature as suitable to be applied in the released data set.
Code: Technique: Bibliography: Data:
SEA-ICE  
I.PP Permittivity by peak-power: effective dielectric constant empirically related to the peak-power Komjathy et al., 2000, Belmonte 2007 P-DM
I.VHP 1st-year thickness VH-phase: inferred from the phase difference between the vertical and the horizontal polarized components Zavorotny and Zuffada, 2002 reflected RHCP and LHCP C-DM
I.POPI Permittivity POPI: from the phase difference between the co- and cross-polar circular polarized components Cardellach et al., 2006, Cardellach et al., 2009 reflected RHCP and LHCP C-DM
I.R Sea-Ice roughness: fitting waveform shape Belmonte 2007 reflected P-DM
SNOW
S.V Volumetric-scattering: resulting from internal reflections between firn layers (sub-structure) Wiehl et al., 2003 P-DM or P-DDM


Table 5: Examples of waveform and waveform required models.
GNSS Bi-Static Radar Equation
General DM, DDM Zavorotny and Voronovich, 2000
Convolution forms Garrison et al., 2002, Marchan et al., 2007
Linear in surface slopes PDF Cardellach and Rius, 2008
EM Scattering Models
KGO e.g. Zavorotny and Voronovich, 2000
KA e.g. Ulaby et al., 1990
SSA e.g. Voronovich 1994
SPM e.g. Rice 1951
Volumetric Scattering
General Ulaby et al., 1990
Ice/Snow Wiehl et al., 2003
Dielectric Properties at L-band
General Ulaby et al., 1990
Soil Vall-llossera et al., 2005
Sea-Ice AGU M. Series 68, 1992, Winebrenner et al., 1989
Sea Surface
Wave spectrum Apel 1994, Elfouhaily et al., 1997
Slopes' distribution Gaussian, bi-normal, Gram-Charlier (Cox and Munk, 1954)
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