Global Navigation Satellite System Reflections Research Articles

LAGRS-Soil: A Full-Polarization GNSS-Reflectometry Model for Bare Soil Applications in FY-3E GNOS-R Payload

The Land Surface GNSS Reflection Simulator (LAGRS)-Soil model represents a significant advancement in soil moisture detection with the aid of Global Navigation Satellite System (GNSS) Occultation Sounder-Reflectometry (GNOS-R) technology, which is one payload of the Fengyun-3E (FY-3E) satellite that was launched on 5 July 2021. To fully exploit the properties of noncoherent scattering, the LAGRS-Soil model has the capability to calculate DDM information for different observational geometries, which relies on the random surface scattering models employed in LAGRS-Soil. This will provide a comprehensive understanding of soil moisture dynamics across diverse terrains and environments. One of the most notable features of LAGRS-Soil is its ability to obtain DDMs for full polarizations, which enhances soil moisture retrievals compared to current methods that only utilize the commonly used LR polarization (left-hand circular polarization received and right-hand circular polarization transmitted). Meanwhile, the model can also capture frozen soil DDMs which holds immense potential for near-surface Freezing/Thawing (F/T) detection, opening up new research and application opportunities in cold climate regions. LAGRS-Soil is built on microwave scattering models, making it a robust and efficient theoretical model for the FY-3E GNOS-R payload. This model can support ongoing soil moisture retrieval efforts by combining physical models with investigations of diffuse scattering and polarization capabilities for soil moisture detection.

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

Global navigation satellite system-reflection (GNSS-R) sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend, which can meet the altimetric precision at the global scale required for underwater navigation. At present, there are still research gaps for GNSS-R altimetry under this mode, and its altimetric capability cannot be specifically assessed. Therefore, GNSS-R satellite constellations that meet the global altimetry needs to be designed. Meanwhile, the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability. Firstly, the GNSS-R constellations altimetric precision under different configuration parameters is calculated, and the mechanism of the influence of orbital altitude, orbital inclination, number of satellites and simulation period on the precision is analyzed, and a new multilayer feedforward neural network weighted joint prediction model is established. Secondly, the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error (RMSE) as 0.0022, which indicates that the prediction capability of the model is excellent. Finally, using the novel multilayer feedforward neural network weighted joint prediction model, and considering the research results and realistic costs, it is proposed that when the constellation is set to an orbital altitude of 500 km, orbital inclination of 75° and the number of satellites is 6, the altimetry precision can reach 0.0732 m within one year simulation period, which can meet the requirements of underwater navigation precision, and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

An Introduction to the HydroGNSS GNSS Reflectometry Remote Sensing Mission

HydroGNSS (Hydrology using Global Navigation Satellite System reflections) has been selected as the second European Space Agency (ESA) Scout earth observation mission to demonstrate the capability of small satellites to deliver science. This article summarizes the case for HydroGNSS as developed during its system consolidation study. HydroGNSS is a high-value dual small satellite mission, which will prove new concepts and offer timely climate observations that supplement and complement the existing observations and are high in ESAs earth observation scientific priorities. The mission delivers the observations of four hydrological essential climate variables as defined by the global climate observing system using the new technique of GNSS reflectometry. These will cover the world's land mass to 25 km resolution, with a 15-day revisit. The variables are soil moisture, inundation or wetlands, freeze/thaw state, and above-ground biomass.

GNSS-IR Model of Sea Level Height Estimation Combining Variational Mode Decomposition

The global navigation satellite system-reflections (GNSS-R) signal has been confirmed to be useful for retrieving sea level height. At present, the GNSS-interferometric reflectometry (GNSS-IR) technology based on the least square method to process signal-to-noise ratio (SNR) data is restricted by the satellite elevation angle in terms of accuracy and stability. This article proposes a new GNSS-IR model combining variational mode decomposition (VMD) for sea level height estimation. VMD is used to decompose the SNR data into intrinsic mode functions (IMF) of layers with different frequencies, remove the IMF representing the trend item of the SNR data, and reconstruct the remaining IMF components to obtain the SNR oscillation item. In order to verify the validity of the new GNSS-IR model, the measurement data provided by the Onsala Space Observatory in Sweden is used to evaluate the performance of the algorithm and its stability in high-elevation range. The experimental results show that the VMD method has good results in terms of accuracy and stability, and has advantages compared to other methods. For the half-year GNSS SNR data, the root mean square error and correlation coefficient of the new model based on the VMD method are 4.86 cm and 0.97, respectively.

Initial GNSS Phase Altimetry Measurements From the Spire Satellite Constellation

AbstractThe collection of phase coherent Global Navigation Satellite System (GNSS) reflected signals from radio occultation receivers in low‐Earth orbit potentially offers the capability of deriving precise altimetry measurements over open and sea‐ice‐covered water at unprecedented coverage and low cost. Although past studies have verified the possibility of deriving altimetric measurements from GNSS observations, there is still uncertainty regarding the precision of this technique and its application. This study highlights the extraction of altimetric information from initial grazing angle GNSS reflection events observed by Spire satellites. Results show that the majority of coherent events occur over sea‐ice‐covered regions. A smaller number of coherent events are observed over the open ocean due to rougher scattering conditions. Altimetric retrieval was performed using dual frequency phase measurements from several events and compared to a model of the sea surface to demonstrate agreement to within 3 cm after the removal of the average height difference.

Sea-Ice Concentration Derived From GNSS Reflection Measurements in Fram Strait

Reflection power derived from the global navigation satellite system (GNSS) observations and its sensitivity to sea-ice concentration are investigated in this article. A corresponding experiment has been conducted during the Fram Strait cruise of the Norwegian research vessel Lance in summer 2016. The dedicated setup with a GNSS Occultation Reflectometry Scatterometry (GORS) receiver and dual-polarization (left- and right-handed) antenna links recorded 1922 h of reflection events during the 20-day cruise of the ship. The antenna setup, mounted 25.0 m above the waterline, serves to acquire sea surface reflections at grazing angles below 30°. Within a 5-min coherent integration period, direct and reflected signal contributions can be separated. Except for the highest sea states, with roll angle changes of 20° peak to peak, the separation allows to retrieve the reflection power and quantifies it in cross-, co-, and cross-to-co-polar ratios. The sea-ice concentration is inverted from power ratios using a non-linear least-squares algorithm. Additional data on sea-ice concentration gathered by a watchman on the ship are used for validation. The inversion results have a 20% resolution in concentration and 3-h resolution in time. The validation shows that the cross- and cross-to-co-polar data are sensitive to the sea-ice concentration. The respective Pearson correlation of 0.75 and 0.67 further suggests studies to foster the application of the GNSS data for sea-ice reflectometry.

Global Ocean Altimetry With GNSS Reflections From TechDemoSat-1

TechDemoSat-1 (TDS-1) is an experimental Global Navigation Satellite System Reflections (GNSS-R) satellite launched in 2014. The GNSS-R receiver onboard performs real-time navigation and generates delay–Doppler correlation maps for Earth-reflected Global Positioning System (GPS) L1 C/A ranging signals. This paper investigates the performance of the TDS-1 data for ocean surface altimetry retrievals. The analysis includes consideration of the transmitter and receiver orbits, time tag corrections, models for ionospheric and tropospheric delays, zenith to nadir antenna baseline offsets, ocean and solid Earth tides, and a comparison with mean sea surface topography. An error budget is compiled to account for each error source and compared with the experimentally derived surface height retrievals. By analyzing data sets covering global ocean surfaces over ±60° latitude, the current performance of spaceborne GNSS-R altimetry with the TDS-1 data set is experimentally established. In comparison with the mean sea surface topography, the surface height residuals are found to be 6.4 m, $1\sigma $ with a 1-s integration time. A discussion of the factors limiting this performance is presented, with implications for future GNSS-R altimetry missions designed for the observation of mesoscale ocean circulation.

Study on Ship-Borne GNSS-R Delay-Doppler Map for Oil Spill Detection

Zhu, X.; Li, Y.; Liu, P.; Liu, B., and Yang Y., 2018. Study on ship-borne GNSS-R Delay-Doppler Map for oil spill detection. In: Wang, D. and Guido-Aldana, P.A. (eds.), Select Proceedings from the 3rd International Conference on Water Resource and Environment (WRE2017). Journal of Coastal Research, Special Issue No. 84, pp. 30–35. Coconut Creek (Florida), ISSN 0749-0208.The intensity of sea surface scattered energy can be mapped with the use of Delay-Doppler Map (DDM) obtained by means of Global Navigation Satellite System-Reflection (GNSS-R) remote sensing technology. It may be applied successfully for oil spills detection. This paper builds a geometrical model for ship-borne GNSS-R double-base sea scattering data analysis exploring the ship-borne specular reflection point and the mean surface slope (MSS) model. The GNSS-R DDM generation algorithm based on the Jacobian determinant method is developed. It is applied for the oil spill DDM simulation using X-band marine radar data of the oil spill accident occurred in Dalian on July 21, 2010. The relationship between the signal characteristics and the oil spill information in DDM is found and the performance of oil spill detection at different wind speed values is analyzed.

Soil Moisture Sensing Using Spaceborne GNSS Reflections: Comparison of CYGNSS Reflectivity to SMAP Soil Moisture

AbstractThis paper quantifies the relationship between forward scattered L‐band Global Navigation Satellite System (GNSS) signals, recorded by the Cyclone Global Navigation Satellite System (CYGNSS) constellation and Soil Moisture Active Passive (SMAP) soil moisture (SM). Although designed for tropical ocean surface wind sensing, the CYGNSS receivers also record GNSS reflections over land. The CYGNSS observations of reflection power are compared to SMAP SM between March 2017 and February 2018. A strong, positive linear relationship exists between changes in CYGNSS reflectivity and changes in SMAP SM, but not between the absolute magnitudes of the two observations. The sensitivity of CYGNSS reflectivity to SM varies spatially and can be used to convert reflectivity to estimates of SM. The unbiased root‐mean‐square difference between daily averaged CYGNSS‐derived SM and SMAP SM is 0.045 cm3/cm3 and is similarly low between CYGNSS and in situ SM. These results show that CYGNSS, and future GNSS reflection missions, could provide global SM observations.

First spaceborne phase altimetry over sea ice using TechDemoSat‐1 GNSS‐R signals

AbstractA track of sea ice reflected Global Navigation Satellite System (GNSS) signal collected by the TechDemoSat‐1 mission is processed to perform phase altimetry over sea ice. High‐precision carrier phase measurements are extracted from coherent GNSS reflections at a high angle of elevation (>57°). The altimetric results show good consistency with a mean sea surface (MSS) model, and the root‐mean‐square difference is 4.7 cm with an along‐track sampling distance of ∼140 m and a spatial resolution of ∼400 m. The difference observed between the altimetric results and the MSS shows good correlation with the colocated sea ice thickness data from Soil Moisture and Ocean Salinity. This is consistent with the reflecting surface aligned with the bottom of the ice‐water interface, due to the penetration of the GNSS signal into the sea ice. Therefore, these high‐precision altimetric results have potential to be used for determination of sea ice thickness.

Monitoring Snow Depth by GNSS Reflectometry in Built-up Areas: A Case Study for Wettzell, Germany

Snow storage dynamics is essential to predict floods, to quantify water resources for human use and irrigation, and to assess the risk of avalanches. Recently, Global Navigation Satellite System (GNSS) ground stations have been successfully used to continuously estimate snow depth at an intermediate scale of about 1.000 $\text{m}^2$ around the stations. In this study, GNSS signal-to-noise ratio (SNR) data at the station Wettzell, Germany, are used to estimate snow depth variations from 2012 to 2015. The station Wettzell is located in a built-up area. The most challenging task at this site is to separate the GNSS reflections from the ground and from surrounding buildings. We modified the interference approach previously used for snow depth estimation using the phase of the multipath interference pattern instead of their frequency. Additionally, we complemented the analysis by including satellites transmitting the L2P signal into the processing. We studied the performance of the L1 signal. The derived GNSS snow depth ranges between 3 and 25 cm and corresponds well to in situ observations by an ultrasonic sensor, with a correlation of 0.8 for daily time series. The residuals of GNSS snow depths compared to the ultrasonic sensor reveal a root-mean-squared error (RMSE) of 4.3 cm for the L2 and 5.9 cm for the L1 signal with a small bias of 1 cm. The results show that the existing data of the global GNSS tracking network promise to provide valuable complementary snow depth observations to the existing sensors at several hundred sites worldwide, including urban areas.

Altimetric algorithm and errors of ocean altimetry using GNSS reflection signals

As a new remote sensing technology, the global navigation satellite system (GNSS) reflection signals can be used to collect the information of ocean surface wind, surface roughness and sea surface height. Ocean altimetry based on GNSS reflection technique is of low cost and it is easy to obtain large amounts of data thanks to the global navigation satellite constellation. We can estimate the sea surface height as well as the position of the specular reflection point. This paper focuses on the study of the algorithm to determine the specular reflection point and altimetry equations to estimate the sea surface height over the reflection region. We derive the error equation of sea surface height based on the error propagation theory. Effects of the Doppler shift and the size of the glistening zone on the altimetry are discussed and analyzed at the same time. Finally, we calculate the sea surface height based on the simulated GNSS data within the whole day and verify the sea surface height errors according to the satellite elevation angles. The results show that the sea surface height can reach the precision of 6 cm for elevation angles of 55° to 90°, and the theoretical error and the calculated error are in good agreement.

Relative Ionospheric Ranging Delay in LEO GNSS Oceanic Reflections

Global Navigation Satellite System (GNSS) reflectometry leverages signals of opportunity to remotely sense the Earth's surface for a variety of science investigations. However, ionospheric refraction affects GNSS reflections detected at low Earth orbit (LEO). While multifrequency GNSS enables the elimination of most of the ionospheric error, single-frequency missions are still susceptible to this ranging delay. Motivated by the planned launch of Cyclone GNSS (CYGNSS) in 2016, a single-frequency reflectometry mission, this letter presents a simulation of the relative ionospheric delay that will shift the Delay-Doppler Map (DDM) data product. A mathematical model is presented that defines and characterizes signal propagation delay in the DDM. The model differentiates direct and reflected signals as a sum of path lengths, atmospheric refraction effects, and noise. We simulate representative ionospheric delays from the model associated with the direct and reflected ray paths as a function of satellite elevation angle, latitude, and solar activity. Simulation using the International Reference Ionosphere 2007 shows that differential ionospheric content is inversely proportional to satellite elevation angle and that low latitudes present larger ionospheric impacts on the reflected signals. Finally, high solar activity conditions lift the ionospheric density profile to and possibly above the CYGNSS orbit altitude of 500 km. The ionospheric delay will not generally affect the estimation of wind speed but may affect the CYGNSS signal acquisition and open loop tracking process. Implications of the ionospheric delay in other GNSS reflectometry applications are also discussed.

SAVERS: A Simulator of GNSS Reflections From Bare and Vegetated Soils

The mean power of the reflected Global Navigation Satellite System (GNSS) signals acquired by a GNSS-Reflectometry (GNSS-R) receiver can be modeled through the integral bistatic radar equation by weighting the contributions of all scatterers on the surface by the system impulse response. The geophysical properties of the scattering surface affect the magnitude of the reflected navigation signals through the bistatic scattering coefficient which, in case the observed surface is land, is a function of the soil dielectric properties, surface roughness, and vegetation cover. In this paper, the GNSS-R signal simulator developed in the framework of the Land MOnitoring with Navigation signal (LEiMON) Project, supported by European Space Agency, is presented. The simulator is able to predict the power reflected by land, taking as input the system and observation parameters, as well as the land surface parameters. The latter are used to simulate both the coherent and the incoherent scattering, taking advantage of widely used theoretical models of bistatic scattering from bare soils and vegetated surfaces. First, the geometrical formulation is discussed, and then, the problem of polarization mismatch due to real antennas at circular polarization is faced following the polarization synthesis approach. Finally, a comparison with some experimental data collected during the LEiMON campaign is presented. The simulations display the same trend of the experimental data, thus showing that the simulator can be used as an efficient tool for the interpretation of GNSS-R measurements.

GNSS-R open-loop difference phase altimetry: Results from a bridge experiment

The paper explores a method to obtain accurate lake surface heights using measurements of the Global Navigation Satellite System (GNSS) carrier phase reflected from the lake surface. The method is referred to as Global Navigation Satellite System-Reflection (GNSS-R) open-loop difference phase altimetry method. It consists of two key technologies: one is the open-loop tracking method to track the GNSS-R signals, where the direct GNSS signal’s frequency is used as a reference frequency to obtain the carrier phases of the GNSS-R signals; the other key technology is time difference phase altimetry method to invert the lake surface heights using two or more carrier phases of GNSS-R signals received simultaneously. A validation experiment is carried out on the SANYING bridge over GUANTING lake using a GNSS-R receiver developed by the Center for Space Science and Applied Research (CSSAR), processing the data with GNSS-R open-loop difference phase altimetry method. The lake surface height results are consistent with the height results of GPS dual-frequency differential positioning altimetry. The results show that we can achieve centimeter level height in one minute average, by using 11 minutes carrier phase data of three GNSS-R signals received simultaneously.

A new technique to sense non-Gaussian features of the sea surface from L-band bi-static GNSS reflections

We present a new technique to analyze L-band signals of the Global Navigation Satellite System (GNSS) that have rebounded off the sea surface, with the aim of retrieving information about surface roughness in the form of the effective Probability Density Function (PDF) of the slopes. Unlike earlier techniques, which parameterize the PDF (usually as normal bivariate distributions), this approach does not constrain the surface slopes' PDF to the shape of a particular analytical distribution. This may help to understand the real information content of L-band scattered signals, which is currently unclear. After validating the algorithm by means of end-to-end simulations, we have applied it to real data. The tests on real data show that the retrievals are robust, consistent with the results obtained with standard GNSS-reflection techniques, and in agreement with independent sources of information. Moreover, the retrieved slopes' PDF present non-Gaussian features, such as skewness. A more in-depth analysis to check whether the skewness is a geophysical signature or an artifact of the technique, shows that it maps with the up-/down-asymmetries introduced by surface forces. In particular, this is the first time that GNSS-reflections have sensed and identified the up- and down-wind signature on the surface, putting and end to the 180° ambiguity that was usually attributed to GNSS observations of directional roughness.

Ionospheric tomography using GNSS reflections

We report a preliminary analysis of the impact of Global Navigation Satellite System Reflections (GNSS-R) data on ionospheric monitoring over the oceans. The focus is on a single polar Low Earth Orbiter (LEO) mission exploiting GNSS-R as well as Navigation (GNSS-N) and Occultation (GNSS-O) total electron content (TEC) measurements. In order to assess impact of the data, we have simulated GNSS-R/O/N TEC data as would be measured from the LEO and from International Geodesic Service (IGS) ground stations, with an electron density (ED) field generated using a climatic ionospheric model. We have also developed a new tomographic approach inspired by the physics of the hydrogen atom and used it to effectively retrieve the ED field from the simulated TEC data near the orbital plane. The tomographic inversion results demonstrate the significant impact of GNSS-R: three-dimensional ionospheric ED fields are retrieved over the oceans quite accurately, even as, in the spirit of this initial study, the simulation and inversion approaches avoided intensive computation and sophisticated algorithmic elements (such as spatio-temporal smoothing). We conclude that GNSS-R data over the oceans can contribute significantly to a Global/GNSS Ionospheric Observation System (GIOS).

The Eddy Experiment: GNSS‐R speculometry for directional sea‐roughness retrieval from low altitude aircraft

We report the retrieval of sea surface directional mean square slope from Global Navigation Satellite System Reflections (GNSS‐R) Delay‐Doppler‐Map (DDM) data collected during an experimental flight at 1 km altitude. We emphasize the utilization of the entire DDM to more precisely infer ocean roughness directional parameters, and argue that the DDM exhibits the impact of both roughness and scatterer velocity. Obtained estimates are analyzed and compared with Jason‐1 measurements, ECMWF numerical weather model outputs and optical data.

Potential of Reflected GNSS Signals for Ice Sheet Remote Sensing

Earth-reflected GNSS (Global Navigation Satellite System) signals have become an attractive tool for remote sensing, e.g., ocean altimetry and scatterometric ocean wind measurements. For ice sheets, the large penetration capability and the large-scale surface averaging of the L-band signals could open a new look on firnpack characteristics like accumulation rates. In this paper we investigate theoretically reflections of GPS (Global Positioning System) signals from ice sheets. We derive a model of the reflection signal and perform simulations of airborne and spaceborne measurements. The results show that the signal, though complex, is sensitive to the roughness of the snow surface (and internal interfaces) and to firn parameters like accumulation rates. To extract valuable and concise information from the complex signal, we derive all example procedure that focusses on particular ground zones during a satellite receiver pass. The results indicate that it should be possible in principle to separately infer surface and firnpack parameters from the measurements. We conclude that GNSS reflections over ice sheets should be further persued, in particular by obtaining experimental data.

POTENTIAL OF REFLECTED GNSS SIGNALS FOR ICE SHEET REMOTE SENSING - ABSTRACT

Earth-reflected GNSS (Global Navigation Satellite System) signals have become an attractive tool for remote sensing, e.g., ocean altimetry and scatterometric ocean wind measurements. For ice sheets, the large penetration capability and the large-scale surface averaging of the L-band signals could open a new look on firnpack characteristics like accumulation rates. In this paper we investigate theoretically reflections of GPS (Global Positioning System) signals from ice sheets. We derive a model of the reflection signal and perform simulations of airborne and spaceborne measurements. The results show that the signal, though complex, is sensitive to the roughness of the snow surface (and internal interfaces) and to firn parameters like accumulation rates. To extract valuable and concise information from the complex signal, we derive an example procedure that focusses on particular ground zones during a satellite receiver pass. The results indicate that it should be possible in principle to separately infer surface and firnpack parameters from the measurements. We conclude that GNSS reflections over ice sheets should be further persued, in particular by obtaining experimental data.