HydroGNSS is a European Space Agency (ESA) 2-satellite mission scheduled for launch in the second half of 2025, equipped to continuously operate dual-frequency, dual-polarization GNSS reflectometry (GNSS-R) receivers. It will also utilize a high-rate complex signal mode, called “coherent channel,” to capture both the in-phase and quadrature components of signals reflected at the specular point during most of the duty cycle. This operation will result in a substantial volume of high-resolution GNSS-R data being available for analysis and applications. The three variables to be provided by the HydroGNSS coherent channel are described here and validated with CYGNSS raw intermediate frequency (IF) signals. The coherence coefficient (CC) and the normalized amplitude (NA), developed from the peak phasors using 4-ms coherent integration time, were compared to the “full entropy” available in the CYGNSS calibrated raw IF product. NA has a similar sensitivity to water surfaces as the full entropy and is not significantly affected by the coherent integration time. CC exhibits a higher sensitivity to small water bodies, yet it strongly depends on the coherent integration time. We also present a new product, the high sampling rate reflectivity (HSRR). It is here defined and compared to CYGNSS${L}1$low rate reflectivity as well as to the high sampling rate (hsr) CYGNSS calibrated raw IF reflectivity, showing a correlation above 0.92. Its effectiveness has been further validated by a physical model, and its uncertainty was preliminarily assessed using data from two nearby tracks. The results demonstrate that HSRR can be a valuable tool for retrieving geophysical parameters, offering a much finer resolution than the 1–2-Hz product.

This paper gives a summary of the HydroGNSS mission and status in the preparations up to launch. Some of the advancements in instrument are presented, including on-board gain adjustment, geolocation. Also the ground processing Payload Data Ground Segment is introduced and some of the processing advances, including antenna pattern modelling for EIRP estimation and bounding of measurement areas.

Monitoring the dynamics and surface conditions of lakes is essential for the understanding of climate change dynamics. Lake water level is one of the variables that needs a particular vigilance, requiring a global and consistent monitoring that can be achieved by spaceborne remote sensing. Satellite radar altimetry has been widely used in the monitoring of inland waters in the past decades, with recent great improvements in the spatial resolution through the new generation of Synthetic Aperture Radar (SAR) altimeters. However, current radar altimetry constellations limits the space-time sampling necessary for a systematic and regular mapping of lakes. GNSS-Reflectometry (GNSS-R) could provide complementary observations to densify the spatio-temporal coverage, allowing hydrologists to access to finer details on the lake surface evolution. In particular, grazing GNSS-R broaden the use of opportunistic GNSS signals due to the smaller elevation angles of the reflecting signals. In this letter we address this issue by comparing the altimetry profiles over Great Lakes of grazing GNSS-R data provided by Spire constellation satellites and SAR altimeter data provided by Sentinel-3 constellation satellites, as a first approach in preparation of inter-techniques hydrology lake water level products. This letter confirms the advantages of fusing observations from both types of remote sensing techniques provided that accurate regional geoid model are available. Furthermore, GNSS-R data could also provide an independent lake water level information to validate the radar altimetry measurements over sites which are not equipped with ground means.

With the evolution of Global Navigation Satellite System (GNSS), more GNSS satellites and civilian signals are available for GNSS Reflectometry (GNSS-R). Developments of new onboard processing strategies can improve the observation performance of spaceborne GNSS-R. To this end, this article proposes a new processing method by coherently combining reflected Global Positioning System (GPS) III L1 C/A and L1C signals. By exploiting the additional signal component, the signal-to-noise ratio of the reflected signal can be significantly improved. Moreover, taking advantage of the narrower auto-correlation function of the combined signal, the spatial resolution and the performance on geophysical applications can be significantly improved. The proposed method has been validated by processing cyclone GNSS (CYGNSS) raw intermediate frequency data including the direct and reflected signals from GPS III satellites. The results indicate that the signal-to-noise ratio (SNR) of the combined reflected waveform can be improved by ~2 dB compared to the L1 C/A waveform. Moreover, the SNR of the combined signal can be improved more efficiently using a longer coherent integration interval compared to the L1 C/A signal. Preliminary altimetric results demonstrate a 35.3%-61.6% improvement in the ranging standard deviation, and a 22.4%-64.4% improvement in the median absolute deviation, compared to L1 C/A measurements. Additionally, the correlation coefficient between combined measurements and wind speed improves by 26.3% on average compared to L1 C/A measurements, and 45.7% for high winds. This article presents a novel GNSS-R onboard signal processing method with improved performance, which can provide a reference for the design of future GNSS-R instruments.

The algorithms to detect the presence of water on land surfaces using the Global Navigation Satellite System (GNSS) reflected signals collected aboard of the future ESA Scout 2-satellite mission HydroGNSS are presented. HydroGNSS will be ready for launch in H2/2024, into polar orbits, and it will operate at dual frequency, dual-polarization, and in two simultaneous acquisition modes (low-rate power and high-rate complex signal modes). The overall strategy to generate level-2, point-by-point along track water classification using all these signals is introduced, yet currently available datasets only permit the validation of the algorithms applied to one single frequency and polarization. Two signal coherence indicators are selected per each acquisition mode, and together with geolocation, large-scale surface roughness, and land cover type are the inputs of the random forest classifier, which is an ensemble learning method, with the monthly Global Surface Water (GSW) as a reference target. The algorithms are tested with NASA/CYGNSS low-rate power delay-Doppler maps (DDMs) and with CYGNSS and U.K./TechDemoSat-1 (TDS-1) raw intermediate frequency (IF) sampled signals. The results of the validation are analyzed at different scales, with results achieving the mission’s 90% accuracy requirement. Final retraining and validation using actual dual-polarization and dual-frequency HydroGNSS data will be conducted once the satellites are in-orbit.

HydroGNSS is the second mission supported by the European Space Agency (ESA) under the Scout program, which is a new framework (3 years from KO to launch, cost ≤ 30 M€) by which ESA aims to demonstrate disruptive sensing techniques or incremental science, while retaining the potential to be subsequently scaled up in larger missions or implemented in future ESA Earth Observation programmes. HydroGNSS consists of a scientific demonstrator that primarily addresses land bio-geophysical variables. The mission is comprised of one satellite (with an option on the second) flying at a low-Earth orbit to collect Global Navigation Satellite System reflections (i.e., Delay Doppler Maps, DDMs) near continuously over the globe. The DDMs are used to generate Level 2 products related to Essential Climate Variables (ECV s), whose estimation defines the primary scientific goal of the mission. In this contribution we outline a review of the ECVs targeted by HydroGNSS, showing some representative results achieved during preliminary studies about the mission. Special emphasis is given to the monitoring of soil freeze-thaw state and soil moisture. ECVs are of great interest and support the sustainable development agenda adopted by the United Nations members in 2015.

This paper presents de development plans of a combined P&L-band reflectometry sensor using signals of opportunity.

The use of Signals of Opportunity (SoOp) is an advantageous way to sense the Earth and ocean surface in a passive bi-static radar configuration, as it allows for smaller sensors compared to active radars. The signals transmitted by the navigation satellites (GNSS) are a good example of SoOP. Several missions using GNSS signals have been launched, e.g. . Using GNSS reflectometry it is possible to obtain estimates of ocean roughness, cryosphere, inland waters or soil moisture, e.g. Other missions using GNSS signals are also being prepared, as for instance, ESA’s second Scout Mission, HydroGNSS [9], which is targeting soil moisture, or ESA’s Pretty mission devoted to altimetry.

This article analyzes the contribution of the delay-Doppler map (DDM) observation noise to the uncertainty of global navigation satellite system reflectometry (GNSS-R) ocean scatterometry observables and the retrieved wind speeds. For this purpose, the parameter$K^{p}$, which is commonly used in the traditional microwave scatterometer, is introduced to characterize the relative standard deviation (RSD) of the GNSS-R normalized bistatic radar cross section (NBRCS) measurement. Based on the noise covariance of the DDM measurements, the analytic expressions of RSD are derived for two cases, i.e., the NBRCS computed with one single DDM bin at the specular point and the NBRCS computed from$M\,\,\times \,\,N$DDM bins around the specular point. By analyzing the dependence of the RSD on different system, geometry, and instrument parameters, the simplified models of RSD are derived empirically. As a simple application of the proposed models, the wind speed retrieval errors are computed using parameters from the Cyclone GNSS (CYGNSS) mission. It shows that the wind speed retrieval error due to thermal noise and speckle can be an important error source for the overall wind speed retrieval performance, especially at high wind speed and with the high incidence angle GNSS-R measurements.

The sensitivity of PAZ’s Polarimetric Radio Occultation (PRO) observations to horizontally oriented frozen particles is assessed using coincident measurements from the Global Precipitation Measurement (GPM) core satellite’s radiometer GPM Microwave Imager (GMI) and ancillary information from Cloudsat. The difference between the horizontal and vertical polarizations of the GMI observed radiances at 166 GHz, indicative of horizontally oriented particles, is compared with the PAZ differential phase shift observations. A clear positive trend is observed, exhibiting a good correlation between the two observations. The radiometer absolute observations and polarization differences (PD) are then used to build a lookup table of ice water content (IWC) vertical profiles, using coincident observations between GPM and Cloudsat. The vertical profiles of IWC, along with the information of the radiometric PDs and some simple assumptions, are used to simulate the expected PAZ differential phase shift observations. The validation with the PAZ and GPM coincident measurements shows a high correlation between the simulated and observed differential phase shift, therefore proving the sensitivity of polarimetric radio occultations to horizontally oriented frozen particles. These results demonstrate that PRO can not only sense the precipitation near the surface (the original goal of the mission) but also the frozen particles near and well above the freezing level, providing additional detail of the cloud vertical structure.

Monitoring freeze/thaw variations of the Earth surfaces is of paramount importance for the study of biogeochemical processes and climate change. At present, the use of passive sensors is well established, but, very recently, some studies demonstrated the potentialities of observations exploiting signals of opportunity. We propose here an advanced study to demonstrate the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to provide accurate and systematic information about the Earth-surface freeze/thaw state. Reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated and compared against the Soil Moisture and Ocean Salinity (SMOS) freeze/thaw product, while state-of-the-art land cover data are used to select GNSS-R data within an estimated footprint. In spite of the limited data availability due to sparse spatial coverage and calibration issues of TDS-1 observations, the proposed analysis demonstrates the possibility of monitoring the freeze/thaw state by analyzing the calibrated reflectivity, including also the possibility of detecting the transition state between frozen and thawed conditions across seasonal variations. This feature makes the design of next-generation GNSS-R satellite missions a unique opportunity to achieve high-resolution freeze/thaw monitoring with small and low-cost platforms.

A tower-based global navigation satellite system reflectometry (GNSS-R) experiment is set up in an Arctic wetland environment for investigating the possibility of monitoring wetland inundation and freeze/thaw (FT) dynamics which are additionally impacted by snow on the ground. Effects of inundation, snow cover, and soil FT state on observed GNSS-R signal-to-noise ratios (SNRs) are analyzed for horizontal (H) and vertical (V) polarizations. A simple classification approach is suggested to detect the inundated, frozen, or thawed soil state. A simple forward reflectivity model is formulated to evaluate the influence of snow cover, overlying frozen, or thawed soil, on the reflected GNSS signals. Reflectivity time series are simulated in H- and V-polarizations usingin situobservations of the Arctic wetland site. The simulations are used to verify the tower-based observations, which show a significant impact of wet snow on reflectivity during melting conditions in spring. The observed SNR is strongly correlated with the Sentinel-1 backscatter coefficient. Generally, soil states detected by GNSS-R are in high agreement with ground truth soil states, especially for inundated and frozen soils. Wet snow conditions, however, complicate the correct timing estimation of soil thawing by inducing reflectivities of a similar order as thawing soil. It is recommended that GNSS-R land application models and retrieval algorithms consider snow cover effects to reduce false classification, especially in FT detection. Overall, the outcome of this study is relevant to the upcoming ESA HydroGNSS mission.

FSSCAT mission was the 2017 ESA Sentinel Small Satellite (S^3) Challenge winner, and the Copernicus masters competition overall winner, and it will be launched in late March 2020. FSSCAT data will provide soil moisture data, sea ice cover and coarse resolution sea ice thickness. FSSCat will be launched for Kourou Space port on June 18th, 2020, 10:51 PM local time. MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) campaign is a one-year long field experiment to study the climate system and the impact of the climate change in the Arctic sea. GNSS-R data from the second leg has been received recently. At the conference the first results of the FMPL-2 payload (combined GNSS-R and microwave radiometer instrument) on board FSSCat will be presented. Preliminary results on the PYCARO-2 GNSS-R instrument in MOSAIC, and model results fed with in-situ auxiliary data are presented in this paper.

In February 2019 a Project Authorization Request was approved by the Institute of Electrical and Electronics Engineers (IEEE) Standards Association with the title “Standard for Global Navigation Satellite System Reflectometry (GNSS-R) Data and Metadata Content”. A Working Group has been assembled to draft this standard with the purpose of unifying and documenting GNSS-R measurements, calibration procedures, and product level definitions. The Working Group (http://www.grss-ieee.org/community/technical-committees/standards-or-earth-observations/) includes members, collaborators, and contributors from academia, international space agencies, and private industry. In a recent face-to-face meeting held during the ARSI+KEO 2019 Conference, the need was recognized to develop a standard with a wide range of operations, providing procedure guidelines independently of constraints imposed by current limitations on geophysical parameters retrieval algorithms. As such, this effort aims to establish the fundamentals of a potential virtual network of satellites providing inter-comparable data to the scientific community.

PRETTY is a 3U Cubesat mission by a consortium of Technical University Graz, Seibersdorf Laboratories and RUAG Space GmbH with a planned launch in 2022. The satellite is based on the OPS-SAT platform [1] and will host two payloads, a radiation monitor and a passive reflectometer. Within the present publication we will discuss the current status of the reflectometer payload including the most relevant risks and also their mitigation by prototype developments and measurements. A first operational version of the instrument using commercial off the shelf (COTS) demonstration boards, hosting flight representative components for the RF front end as well as for the digital signal processing has been assembled and integrated with the corresponding hard- and software. While measurement results based on using the output of a global navigation satellite system (GNSS) simulator as input to the PRETTY instrument have been presented earlier, we focus within this publication on the result of field tests on representative hardware in order to evaluate the expected L1 band environment for the mission.

This article assesses the ocean altimetry performance of spaceborne Global Navigation Satellite Systems reflectometry (GNSS-R) by processing the raw data sets collected by the Cyclone GNSS (CYGNSS) constellation. These raw data sets, i.e., the intermediate frequency signal streams before any receiver processing, are processed on the ground with a software receiver, from which the reflected waveforms of GPS L1, Galileo E1, and BeiDou-3 B1 band open service (OS) signals are generated following the conventional GNSS-R approach. By using different retracking algorithms, the bistatic delays of the reflected signals are derived from these waveforms, in which the retracking biases are removed with the specular point (SP) delay and power information computed from the corresponding waveform model. After applying a set of standard delay corrections, the bistatic delay observations are converted into sea surface height (SSH) measurements and compared with the mean SSH model. Both the random error (precision) and systematic effects (accuracy) are characterized with intratrack and intertrack analyses of the bistatic delay measurements. The two-way ranging precision can reach up to 3.9 and 2.5 m with 1-s GPS and Galileo group delay measurement (a factor of ~2 better for altimetry solution), and its evolution with the signal-to-noise ratio shows good consistency with the theoretical model. A significant delay dispersion of 3.0 m between different tracks is found, which is mainly attributed to the receiver orbit error and ionospheric correction residuals. These results can provide useful inputs for the development of future GNSS-R missions dedicated to ocean altimetry applications.

Passive remote sensing from space with signals of opportunity has been studied for a long time beginning in the early 90s [1]. The technique uses already existing signals, transmitted from satellites, which are reflected from ground in order to determine properties of earth surface. GNSS signals are the main interest here, due to their well-known signal properties. The Passive reflectometer acts as a bistatic radar, hence no expensive and power-consuming radar transmitter are needed. The received signal is correlated with a local code replica, where the resulting waveform shows properties of the reflected surface area. Instead of using a local code replica, the PRETTY mission will correlate the received reflected signal with the received direct signal. This technique is known as the interferometric approach. The main advantage for the interferometric approach is, that one is not bound to use known signals but can also exploit signals with unknown data modulation, opening up the possibility to use more generic signals for earth observation.The PRETTY satellite architecture will be based on the OPS-SAT architecture with modifications to accommodate the two payloads. RUAG Space GmbH as prime contractor will design the passive reflectometer payload, and Seibersdorf Laboratories is responsible for a novel dosimeter payload for measuring the space radiation environment during the PRETTY space mission. The dosimeter system will assess Total Ionizing Dose (TID) by the use of radiation integrating sensors, as well as LET spectral information, which is related to Single-Event Effects (SEE) in electronic components. Technical University Graz contributes the satellite platform based on the OPS-SAT architecture [2]. Furthermore TU Graz conducts the Manufacturing, Assembly, Integration and Test (MAIT) activities and will be in charge for the operation of the satellite. The scientific advisory group to be established will support the design of the payload and the evaluation of the raw data from the operation of the satellite. Within the present paper we will describe the architecture of the passive reflectometer payload within this 3U CubeSat mission and discuss operational routines and constraints.

This work aims to demonstrate the applications of spaceborne Global Navigation Satellite System reflectometry (GNSS-R) over inland waters and wetlands. Raw samples of the GNSS signals reflected from lakes, rivers and wetlands have been recorded occasionally by the TechDemoSat-1 (TDS-1) and Cyclone GNSS (CYGNSS) missions. Strong coherent reflections have been found in the GNSS-R signals from open inland water bodies (lakes and rivers), which would make possible to perform precise surface altimetry measurements using both group delay and carrier phase from reflected signals. In addition, it is also found that GNSS signals reflected off densely vegetated wetlands also present some coherent features from the evolution of their carrier phase, showing the potential of the GNSS-R technique to monitor extremely dense wetlands from spaceborne platforms.

Arctic and Antarctic sea ice covers are in a sharp contrast in terms of characteristics, distributions, and processes with a drastic decrease in the Arctic versus the opposite increase in the Antarctic in a changing climate. In quantifying polar sea ice differences to address the contrasted sea ice behaviors, two key parameters are sea ice thickness and melt pond fraction, which remain challenging to measure extensively in time and in space with a sustainable approach. Here, we present a new paradigm for such measurements using bistatic radar reflectometry, thanks to developments of low-cost receivers to acquire reflected signals from numerous existing transmitter systems operated at multiple frequencies to be replenished and sustained indefinitely into the future. For sea ice thickness measurement to determine ice volume, reflected signals likely come from the bottom ice-water interface avoiding large errors inherent in current altimetry techniques due to uncertainty in free-board height and snow cover. Regarding melt pond faction on sea ice to estimate albedo and insolation, the bistatic reflection can be dominated by melt pond water with permittivity that is one order of magnitude larger compared to that of snow or ice. These are examined by a combination of numerical Kirchhoff (KA) simulator and Numerical Maxwell Model of 3D simulations (NMM3D) to preserve phase and amplitude information and thereby account for both coherent and incoherent effects. Physical insights from the rigorous theory for bistatic radar reflectometry will be valuable to develop future satellite missions to resolve cryospheric science issues concerning the polar sea ice differences.

In global navigation satellite systems reflectometry (GNSS-R), the autocorrelation property of the transmitted GNSS signal is an important factor in the delay-Doppler map of the scattered power. The autocorrelation functions (ACFs) of the GPS Level 1 (L1) coarse/acquisition signals exhibit sidelobes. For some of the pseudorandom noise (PRN) codes, the high-amplitude sidelobes are located within one chip from the main lobe and, thus, broaden or narrow its width. These PRN-dependent ACF deviations can introduce significant biases into the GNSS-R scatterometric observables and the wind speed measurements. Simulation results for Cyclone GNSS (CYGNSS) mission show that the ACF deviation induced wind speed error can be larger than 10% (e.g., 2-3 m/s for 20 m/s and 7-8 m/s for 40 m/s wind speeds). These effects can be corrected efficiently by applying empirical factors on the CYGNSS L1 observables.

This work is to demonstrate spaceborne altimetry over sea ice using coherent component of reflected Global Navigation Satellite System (GNSS) signal. The raw samples of sea ice reflected GNSS signal collected by the UK TechDemoSat-l (TDS-l) mission are processed. Strong coherent components are found in sea ice reflected GNSS signal received in space at different elevation angles, which would make it possible to perform precise surface altimetry measurements using the carrier phase information of the reflected signals. In addition, the coherent reflected signals can be integrated coherently for a longer period to increase the signal to noise ratio, which would make it possible to demonstrate the interferometric GNSS-R (iGNSS-R) altimetry technique in space without very high gain antenna. In this presentation, the altimetric results of coherent GNSS reflections with both carrier phase and code phase will be discussed.

The experiment called Radio-Occultation and Heavy Precipitation aboard PAZ (ROHP-PAZ) is the first attempt to perform spaceborne polarimetric radio-occultations (PRO) with signals transmitted by the Global Navigation Satellite Systems (GNSS). The GNSS payload aboard PAZ, initially intended for precise orbit determination, was extended with a dedicated two-polarization Radio-Occultation (RO) antenna pointing to the limb of the Earth and the receiver was upgraded to track occulting signals. The experiment is a proof-of-concept for heavy rain measurements using polarimetric GNSS RO. The PAZ satellite was launched in February 22, 2018. Preliminary results from the commissioning phase will be presented.

We present a new passive bi-static radar measurement concept that employs digital satellite TV signals transmitted from geostationary orbit as signals of opportunity to measure precipitation. We also present experimental results using artificial targets, and provide results on measured Doppler frequencies as well.

This paper analyzes the ocean altimetry precision of global navigation satellite systems' reflectometry (GNSS-R) by characterizing the noise statistics of the measured waveform. For this purpose, we first investigate the dependence of the altimetry precision on the statistics of the observed waveform and then derive an analytical model of the waveform statistics after incoherent averaging. The main data set used for altimetry analysis and model validation is the GPS L5 signals obtained from an airborne experiment. Two different delay estimators, based on the leading-edge derivative (DER) and the waveform fitting (FIT) over the leading edge, have been implemented. Later, the relationship between the statistics of the observed waveform and the altimetry precision is derived and validated for both the estimators with the airborne data. Then, the analytical model of the statistics of the incoherently averaged waveform is built from the correlation properties of the complex waveform, and also validated with both airborne and the TechDemoSat-1 spaceborne data. After that, the proposed waveform statistics and altimetry precision models are applied to spaceborne cases with different orbit altitudes. The altimetry performance of different onboard processing methods, i.e., conventional GNSS-R and interferometric GNSS-R, and delay estimators, i.e., DER and FIT, are preliminarily assessed. Finally, the dependence of altimetry precision on different parameters is analyzed and a simplified model of altimetry precision is proposed for the spaceborne case.

The Global Navigation Satellite System (GNSS) polarimetric effects on the propagation of radio occultations (ROs) are studied here. Polarimetric ROs have been suggested as a technique to detect heavy rain events using opportunity signals from GNSS satellites. The systematic effects that hinder the isolation of the precipitation information are described and their significance and separability are assessed. A method that relies on the received phase difference between polarizations is presented. A dual-frequency extension is capable to completely separate the hydrometeor information from the other effects, including the ionospheric influence.

Characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage require information about wetland dynamics, which remains a major gap in existing knowledge. Despite recent advances in satellite monitoring techniques, dynamic wetland mapping needs to be improved for more accurate global inventories and also to monitor variabilities at sub-km scale over multiple decades. It has been shown that Global Navigation Satellite Systems (GNSS) Reflectometry (GNSS-R) signatures off inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. In this study, we will further investigate the capabilities of the GNSS-R technique for wetland monitoring from aircraft platforms.

Due to the launch of a number of dedicated GNSS-R satellite missions during the last years, there is a potential raise of research interest in this field. This paper presents an analysis and simulation tool for the GNSS-R community: wavpy. More than just a simple waveform simulator, this library provides a set of object-oriented classes dedicated to each of the different elements that characterize a GNSS-R scenario. Then, the user can focus on just a particular piece of analysis or, by exploiting their combined synergies, to perform a more comprehensive simulation exercise.

This work is to analyse the ocean altimetry precision of Global Navigation Satellite Systems Reflectometry (GNSS-R) based on the statistics of observed waveform. The GPS L5 signals obtained from an airborne experiment are used for this study. The altimetry precision is analysed for two specific algorithms, based on the leading edge derivative (DER) and the leading edge fitting (FIT), in which the relationship between the altimetry precision and the waveform statistics is established and validated. Then, we introduce an analytical model of the statistics of the incoherently averaged waveform, which has been validated with both airborne and spaceborne data. Finally, as an example, the altimetry precision is predicted for the GEROS-ISS mission, and preliminary results are presented.

Since the nadir 1-second altimetry precision was first estimated to be of 56 cm when the PARIS concept was developed back in 1993 (it was assumed the interferometric processing of GPS P-code signals and a 4×4 m×m receiving antenna at 700 km orbital altitude) [1], many detailed analyses and experiments have been conducted leading to far more optimistic values, as low as some 15 cm (using the interferometric processing and a 1 m2antenna from 400 km altitude). This paper presents the instrument and concept advances that have allowed such improved expectations.

The Software PARIS Interferometric Receiver (SPIR) was conceived as a multiple beam-forming GNSS-Reflectometry receiver capable of implementing different signal processing strategies (clean-replica, interferometric, etc.) in order to demonstrate the synoptic capabilities for sea-surface altimetry using the interferometric GNSS-R technique. The instrument has been designed as a 16-channel very-high speed (320 MB/s) hardware recording receiver followed by a software post-processor, implementing the beam-forming and signal processing. The presence of 16 channels together with the beam-forming capabilities requires to characterize the quantization offsets, instrument time-keeping and relative instrumental delays between the different channels in order to have a well-functioning instrument. In this paper we present several calibration aspects of SPIR.

We present in this paper the work done to test the synoptic capabilities of the GNSS-R interferometric technique as a means towards sea surface altimetry estimation, which is an integrated part of the assessment of the GEROS-ISS mission. For this purpose, a new software receiver has been developed and tested: SPIR. With the lessons learned after a first flight campaign, some system modifications were performed and a second experimental campaign has been recently carried on. Initial results show interferometric waveforms that present the quality required for altimetric analysis.

The Software PARIS Interferometric Receiver (SPIR) is a multichannel GNSS-R recording receiver. It is capable to record the GNSS signals at L1, L2 or L5 bands from eight up-looking and eight down-looking antenna elements simultaneously at a rate of 80 MHz. A software post-processor processes the recorded data off-line to obtain altimetric estimates. Its development has been carried out in order to validate experimentally the synoptic capabilities of GNSS-R using the PARIS Interferometric Technique and to allow the comparison of different GNSS-R processing techniques on exactly the same set of recorded data. The paper presents the instrument's main characteristics and preliminary results.

GEROS-ISS (GEROS hereafter) stands for GNSS REflectometry, Radio Occultation and Scatterometry onboard the International Space Station. It is a scientific experiment, proposed to the European Space Agency (ESA) in 2011 for installation aboard the ISS. The main focus of GEROS is the dedicated use of signals from the currently available Global Navigation Satellite Systems (GNSS) for remote sensing of the System Earth with focus to Climate Change characterisation. The GEROS mission idea and the current status are briefly reviewed.

The Global Navigation Satellite System (GNSS) reflectometry, i.e. GNSS-R, is a novel remote-sensing technique first published in [1] that uses GNSS signals reflected from the Earth's surface to infer its surface properties such as sea surface height (SSH), ocean winds, sea-ice coverage, vegetation, wetlands and soil moisture, to name a few. This communication discusses the scientific value of GNSS-R to (a) furthering our understanding of ocean mesoscale circulation toward scales finer than those that existing nadir altimeters can resolve, and (b) mapping vegetated wetlands, an emerging application that might open up new avenues to map and monitor the planet's wetlands for methane emission assessments. Such applications are expected to be demonstrated by the availability of data from GEROS-ISS, an ESA experiment currently in phase A [2], and CyGNSS [3], a NASA mission currently in development. In particular, the paper details the expected error characteristics and the role of filtering played in the assimilation of these data to reduce the altimetric error (when averaging many measurements).

A Global Navigation Satellite System (GNSS) radio occultation (RO) experiment is being accommodated in the Spanish low Earth orbiter for Earth Observation PAZ. The RO payload will provide globally distributed vertical thermodynamic profiles of the atmosphere suitable to be assimilated into weather numerical prediction models. The Ground Segment services of the U.S. National Oceanographic and Atmospheric Administration and standard-RO processing services by University Corporation for Atmospheric Research (USA) will be available under best effort basis. Moreover, the mission will run, for the first time, a double-polarization GNSS RO experiment to assess the capabilities of polarimetric GNSS RO for sensing heavy rain events. This paper introduces the Radio-Occultation and Heavy Precipitation experiment aboard PAZ and performs a theoretical analysis of the concept. The L-band GNSS polarimetric observables to be used during the experiment are presented, and their sensitivity to moderate to heavy precipitation events is evaluated. This study shows that intense rain events will induce polarimetric features above the detectability level.

This paper revises the precision of altimetric measurements made with signals of the Global Navigation Satellite Systems (GNSS) reflected (GNSS-R) off the sea surface. In particular, we investigate the performance of two different GNSS-R techniques, referred to here as the clean-replica and interferometric approaches. The former has been used in GNSS-R campaigns since the late 1990s, while the latter has only been tested once, in 2010, from an 18-m-high bridge in static conditions and estuary waters. In 2011, we conducted an airborne experiment over the Baltic Sea at 3-km altitude to test the interferometric concept in dynamic and rougher conditions. The campaign also flew a clean-replica GNSS-R instrument with the purpose of comparing both approaches. We have analyzed with detail the data sets to extract and validate models of the noise present in both techniques. After predicting the noise models and verifying these with aircraft data, we used them to obtain the precision of altimetric measurements and to extrapolate the performance analysis to spaceborne scenarios. The main conclusions are that the suggested noise model agrees with measured data and that the GNSS-R interferometric technique is at least two times better in precision than a technique based on using a clean replica of the publicly available GPS code. This represents a factor of at least four times finer along-track resolution. A precision of 22 cm in 65-km along-track averaging should be achievable using near-nadir interferometric GNSS-R observations from a low earth orbiter.

A bistatic radar at X-band (11 GHz) using opportunity signals (Passive Reflectometry and Interferometry System (PARIS) concept implementing the interferometric technique) has been developed and tested in a coastal-based experimental setup. Digital satellite TV signals broadcast from geostationary orbit have been used as sources of opportunity, and correlation waveforms have been collected at different receiver bandwidths. Calibration algorithms to compensate instrumental errors have improved our observables and allowed us to obtain delay measurements with a precision of about 10 cm for wind speeds in the range of 3 m/s. A statistical analysis of the measurement noise is used to determine the quality of the obtained observables. This paper also discusses the opportunities of the PARIS concept applied at higher frequency band and with stronger signals.

We report preliminary results of an aircraft experiment aimed to proof the PARIS Interferometric Technique. The experiment was performed in the Gulf of Finland during a two hours flight. We installed a PARIS Interferometric Receiver together with a GOLD-RTR instrument to collect reflected C/A, P(Y) and M-code GPS signals. The collected data has been analyzed to produce altimetric observables with both techniques.

This paper evaluates the potential use of reflected signals from Global Navigation Satellite Systems as a source of opportunity for the retrieval of absolute ellipsoidal heights over sea ice. Accurate estimation of the surface level would be helpful for the determination of the ice thickness, a key parameter for classification and characterization of sea ice masses. Our analysis is based on altimetric estimations from the coherent differential phase between direct and both cross- and co-polar reflected signals. For this purpose, GPS waveforms have been collected from a fixed platform in Greenland, monitoring the complete process of sea ice formation and melting during a 7-month period. The variability of coherent phase samples and polarimetric measurements are compared with in situ observations to make a realistic rough characterization of the ice cover. The retrieved sea ice surface height estimates are then evaluated against an Arctic tide model, ice surface temperature from moderate-resolution imaging spectroradiometer, and the laser altimetry product from ICESat.

We present in this paper an empirical approach for the characterization of the internal layering of dry snow masses by means of GNSS-R. A forward model has been designed for reconstructing reflected waveforms given a dry snow profile and geometry (elevation and elevation-rate), as a sum of multiple responses from different layers. To extract the internal information, Fourier transforms of time series of waveforms are computed to generate lag-holograms. The frequency stripes that appear are related to the depths of the contributing snow layers. The same analysis has been done with real data, showing with agreement with the models.

A Global Navigation Satellite System (GNSS) Radio-Occultation (RO) experiment is being accommodated in the Spanish Low Earth Orbiter (LEO) for Earth Observation PAZ. The RO-payload will provide globally distributed vertical thermodynamic profiles of the Atmosphere in Near Real-Time (NRT) suitable to be assimilated into Weather Numerical Prediction Models. The NRT operability will be dispensed by the Ground Segment services of the U.S.A. National Oceanographic and Atmospheric Administration (NOAA). Moreover, the mission will run, for the first time from Space, a double-polarization GNSS experiment, to assess the capabilities of polarimetric GNSS-RO for detection of heavy rain events.

GPS reflected signals have become a source of opportunity for remote sensing of the Earth's suface. In this work, we present several capabilities of this technique in two different polar environments: Greenland and Antarctica. The first part is dedicated to the retrieval of sea-ice properties, giving emphasis to the study of the coherent phase for altimetric and roughness estimations, and polarimetric measurements for the determination of the ice salinity variation. The results show good agreement with a tide model and daily ice charts. On the second part, some preliminary results and analysis strategies to retrieve dry snow signatures are presented.

A proof-of-concept instrument for PARIS-IOD, based on a full-custom dedicated GNSS-Reflections receiver has been developed, and the novel interferometric concept tested in several experiments using signals generated by a SPIRENT equipment. The preliminary analysis has resulted in the detection of 1-cm delay-jumps, using 33 group-delay observables of 1 second, with an associated dispersion of the order of 2-cm. A signal-to-noise degradation of the order of ~3 dB with respect to the one expected for the Bridge Experiment would keep the 1-second sigma error below 3-cm.

We describe the development and implementation of a method for extracting altimetric information using the Passive Reflectometry and Interferometry System (PARIS), i.e., from GPS signals after their reflection off the sea surface. We have formalized one idea laid out in the description of a bistatic system for ocean altimetry using the GPS signal, by Hajj and Zuffada (Jet Propulsion Laboratory), and have extended it to real situations encountered in PARIS aircraft experiments. Second, we have developed the corresponding algorithms to produce real-time altimetric observables to be used in dedicated digital signal processors. Finally, we have applied this method to estimate sea-surface height from one flight experiment in the North Sea off the coast of Norway.

The CAROLS, L band radiometer, is built and designed as a copy of EMIRAD II radiometer of DTU team. It is a Correlation radiometer with direct sampling and fully polarimetric (i.e 4 Stockes). It will be used in conjunction with other airborne instruments (in particular the C-Band scatterometer (STORM) and IEEC GPS system, Infrared CIMEL radiometer, one visible camera), in coordination with in situ field campaigns for SMOS CAL/VAL. The instruments are implemented on board the French research airplane ATR42. A validation campaign with four flights was made over south west of France, Hourtin Lake and Bay of Biscay (Atlantic Ocean) in September 2007. In order to qualify the radiometer data, different types of aircraft movements were realized: circle flights, wing and nose wags. Simultaneously to flights, different ground measurements were made over continental surfaces and ocean. First results show a good quality of data over ocean surfaces. For continental surfaces, important Radio-Frequency Interferences (RFI) were observed over a large part of the studied region.

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 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. 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, that maps with the up-/down- asymmetries introduced by surface forces. This is the first time that GNSS-reflections have sensed and identified the up- and down-wind signature on the surface.

The technological aspects of the Altimetric and Scatterometric Applications of PARIS (ASAP) sensor are presented in this paper. This sensor is based on the PARIS concept, which makes use of GPS signals reflected on the ocean's surface in order to measure the surface's properties (altitude and roughness). The ASAP instrument is a hardware real-time PARIS receiver with the aim of being an intermediate step between the airborne GOLD-RTR receiver developed at our institute and a future spaceborne PARIS instrument.

This paper describes a new instrument that was specially designed and developed to gather global positioning system (GPS) signals after they have been reflected from suitable surfaces (sea, ice, and ground), for Earth remote sensing. The device has been called the GPS open-loop differential real-time receiver (GOLD-RTR). Its main and most innovative feature is its computation and storage, in real time, of complex-valued ($I$and$Q$) cross correlations (waveforms) between GPS L1-C/A signals—received directly and after reflection—and the corresponding models of these signals. Particularly, the GOLD-RTR schedules consecutive coherent integration time slots of 1 ms over which ten parallel correlation channels, with 64 lags each, work simultaneously and continuously with the input raw data sampled at 40 MHz. The total throughput is 10 000 waveforms per second, each waveform being 64 lags long. These real-time correlation resources can be flexibly distributed in several configurations according to the observational requirements, for instance: Doppler/delay maps or up to ten simultaneous reflected waveforms for ten different GPS satellites are examples of what can be done. The further processing of the real-time computed 1-ms waveforms in a flight campaign over the ocean, ice, or ground can be used to obtain geophysical parameters such as sea level and tides, sea surface mean-square slopes, ice roughness and thickness, soil moisture and biomass, or future applications. This paper covers the GOLD-RTR architecture and hardware, signal processing and data storage issues, machine–user interface, laboratory readiness tests, and waveform data samples from the first two jet aircraft campaigns at 9300 m over the sea.