This study presents a Digital Twin (DT) that is being created to optimize the use of the available hydric resources, and mitigate the effects of the increasing water shortage in irrigated agriculture in fields in the Urgell channel region (Lleida). A DT is "a virtual representation of an object or system that spans its lifecycle, it is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making." It will model the water fluxes using the knowledge of the amounts of water taken in, used, and returned to the environment, and other parameters that impact the water budget, such as atmospheric variables (temperature, water vapor deficit, relative humidity, solar radiance…), surface soil moisture, and evapotranspiration maps, etc. Satellite Earth Observation (EO) data, collocated with in-situ data from a network of 20 soil moisture probes and 2 meteo stations will be used to train the DT. Additionally, a rover-based ground penetrating radar will be used for cross-calibration.

Numerous studies have demonstrated the effectiveness of CYGNSS data for flood detection and mapping. However, the vast majority of the studies only focuses on flood extent detection, ignoring the importance of flood water levels in post-disaster relief. Meanwhile, most of the existing studies on inland water levels altimetry using CYGNSS data are based on the CYGNSS raw IF data using either the time-delay method or the phase method for altimetry. Although high accuracy can be obtained, at present the CYGNSS raw IF data is not a standard data, so it cannot be applied to the study of emergency flooding events. Given the above research gaps, this study proposes an effective method to combine CYGNSS L1 standard data with DTM for rapid estimation of flood water levels. The effectiveness of the proposed methodology is validated using the case of the 2022 Pakistan mega-flood. Comparison with ICESat-2 altimetry data gives encouraging results.

Global Navigation Satellite System Reflectometry (GNSS-R) is a remote sensing technology that uses GNSS signals reflected over Earth’s surface, offering advantages such as high spatio-temporal resolution and cost-effectiveness. GPS navigation signals convey navigation information through the navigation bits, in which phase jumps occur randomly at 20 ms interval. However, navigation information is meaningless in GNSS-R and limits the coherent integration time. This study presents a technique to mitigate the impact of the navigation bits on the generation of DDMs by using the raw GNSS-R data from the Fengyun-3E (FY-3E) satellite. Sample results show that, after correcting for the navigation bits, the signal-to-noise ratio (SNR [dB]) of DDMs increased by ~0.4 dB over sea to up to 3 dB over sea ice, showing that this improvement is very significant for coherent targets. The proposed navigation bit correcting method in this study significantly improves the usability of these DDMs, and opens the door to other applications that require larger integration times.

Lithosphere-Atmosphere-Ionosphere coupling models have been widely studied and applied to earthquakes and their potential precursors. Recent evidence has been found that electromagnetic phenomena related to earthquakes might produce ionospheric anomalies even before their occurrence. This study analyzes their correlation focusing on the ionospheric scintillation associated to seismic activities in 2022 in the area around the Coral Sea. Among all the ionospheric indicators, this study analyzes the S4scintillation index from COSMIC-2 GNSS Radio Occultation (GNSS-RO), to estimate the ionospheric perturbation and identify anomalies. Two cases of earthquakes in 2022 with magnitudes larger than 6 are presented showing the positive correlation between the ionospheric scintillation and earthquake precursors.

The ionospheric scintillation can be explained as the fluctuations in the phase and intensity of electromagnetic rays after crossing the ionosphere. Rino’s theory was proposed in 1979 to quantify this scintillation, and subsequent models appeared to predict its characteristics. One of them is the WideBand ionospheric scintillation Model (WBMOD) from 1984. This study aims to provide a neural network that emulates the behavior of WBMOD model, by learning from phase and intensity scintillation data gathered from several ESA projects. By using the Rino’s power-law phase-screen ionospheric scintillation theory, the values of the height-integrated irregularities strength (CkL) and the slope of its PSD (q) can be obtained from the physically measured S4and σϕ. So, using this data, two neural networks are presented which obtains results that fit well with the WBMOD expected values.

From 1998 to 2022, Earthquakes have caused more than 850 thousand deaths and US$ 700 billion in economic losses. At this time, there is no reliable precursor to predict them. Many studies have attempted to link Land Surface Temperature (LST) anomalies to earthquake occurrence. This study uses long-term datasets from FengYun-2F/VISSR (Visible and Infrared Spin Scan Radiometer) sensors [1] between 2014 and 2022 to analyze the extent of LST anomalies and their potential link to earthquakes. More than 14,000 land and coastal earthquakes of magnitude higher than M4 have been studied between [+40°, +140°] longitude. Three methods frequently used in the literature, the Standard Deviation (STD), the Interquartile (IQT), and the Z-Score techniques have been implemented to detect LST anomalies on temporal series. Other parameters, such as the confusion matrix and the Receiver Operating Curves (ROC), have also been computed to assess and improve their performance and select the optimum correlation threshold. A positive LST anomaly is typically found before the earthquakes, followed by an LST decrease after the event.

This study presents a new signal processing method to mitigate RFI, based on the Karhunen-Loève Transform. The main property of this method is that it is adaptive and RFI-agnostic – i.e., it is able to potentially mitigate any type of RFI waveform. It is based on the estimation of the covariance matrix of the process, and the derivation of a basis that spans the RFI subspace. The methodology to find this basis is explained in detail. The theoretical performance obtained using KLT is explored by simulations, along with the evaluation of the influence of the system parameters. In addition, a couple of examples with real data are provided.

Significant Wave Height (SWH) is a key parameter to characterize waves, which is typically used in sea state monitoring such as wave forecast to ensure ocean navigation safety. Satellite radar altimeter is probably the primary tool to obtain SWH information. However, it cannot be used for large-scale sea state monitoring unless many of theses satellites are deployed. In this article, we aim to study the potential of Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) in SWH measurement based on spaceborne Delay-Doppler Maps (DDMs) data. First, 3 observables (i.e., Delay-Doppler Map Average (DDMA), leading edge slope (LES) of normalized integrated delay waveform (NIDW) (LES-NIDW), and trailing edge slope (TES) of NIDW (TES-NIDW) derived from the DDMs are introduced for SWH estimation. Then, an empirical SWH retrieval model is proposed based on three observables. Subsequently, ERA5 SWH is used as reference data to verify the performance of the proposed model. The experimental results show that the Root Mean Square Error (RMSE) and Correlation Coefficient (CC) estimated by SWH of the three observables are better than 0.54 m and 0.88 m, respectively. Among them, the estimation performance based on DDMA observable is the best, with RMSE and CC of 0.49 m and 0.89 m. This study shows the potential of spaceborne GNSS-R in SWH retrieval.

GNSS-R (Global Navigation Satellite Systems Reflectometry) can be understood as a multi-static radar with as many transmitters as navigation satellites and in view and can be tracked. GNSS-Reflectometers can process the reflected signals as a scatterometer, as an altimeter, or as an unfocused synthetic aperture radar. GNSS-R has demonstrated its potential to infer numerous geophysical variables over land (soil moisture, vegetation height, detecting freeze-thaw states... ), over the ocean (wind speed and direction, significant wave height, sea surface altimetry... ), over sea ice (extent, depth, type... ). Even a marine plastics litter product has been recently released by NASA, and some have suggested that sea surface salinity could also be inferred. In scatterometric applications the most widely used GNSS-R observable is the peak of the Delay Doppler Map (DDM), and many efforts have been directed towards an accurate instrument calibration. However, many geophysical parameter retrievals have neglected some variations of the DDM linked to the observation geometry, as well as the sensitivity to other geophysical variables. In this study we present analyze some of these effects and present a sensitivity analysis for the ocean case, notably the impact of the wind direction (WD), the 10 m height wind speed (mathrm{U}-{10}), which is routinely obtained today from GNSS-R observables, the sea surface temperature (SST) and sea surface salinity (SSS), and the presence of oil slicks. This quantitative study illustrates the challenges presented to retrieve some of these variables, the required corrections and their accuracy.

Today hyperspectral imagers are capable to capture hundreds of spectral bands simultaneously, while they are getting smaller, fitting in CubeSats. The huge amount of information provided by these sensors is used for numerous studies, and it can be used to infer multiple variables. However, the huge data volume generated is difficult to be managed by large satellites, and it is almost impossible in the smaller ones. This work presents a low resource consuming unsupervised band selection algorithm that uses only the information of the captured image, and no further auxiliary information. It can be used to reduce the amount of data to be downloaded, while controlling the performance degradation. © 2022 IEEE.

Passive microwave remote sensing encompasses techniques well suited for use in systems with limited power budget, due to the low consumption linked to reception-only operation. Some examples of these techniques include Microwave Radiometry (MWR), Global Navigation Satellite Systems Reflectometry (GNSS-R), and Radio-Frequency Interference (RFI) detection algorithms. Small satellite missions including these instruments, such as FSSCat, have proven the value of passive remote sensing techniques with high revisit times due to the low orbits, and the possibility to horizontally scale the mission with more satellites. The Flexible Microwave Payload (FMPL) used in the FSSCat mission has continued development within the RITA Payload project, and it is now being used in Drone-based platforms to provide in-situ data using space-proven acquisition algorithms. In this work, the development of a drone-based FMPL will be presented.

Recent studies have shown possible signatures or precursors of seismic activity in the ionosphere. Our group is focusing on ionospheric scintillation associated with seismic activity. By the time this study was conducted, the sudden volcanic eruption in the Spanish La Palma island, starting on September 19th, opened a possibility to study the impact of this exceptional, well time-defined seismic event on the iono-sphere and the radio-wave propagation through it. A complete study measuring scintillation on GNSS signals and its correlation to seismic activity is presented in this extended abstract. In particular, scintillation data from two ground stations in the Canary Islands, NASA CYGNSS GNSS-Reflectometry and Spire GNSS Radio-Occultation measurements have been used. A linear correlation analysis has been conducted between S4, and the earthquakes generated energy in 6 h intervals. Small, and slightly positive regression coefficients have been found with almost all methods.

Annually, earthquakes cause human and material losses. For instance, between 1998 and 2018, 846 thousand deaths and about US$ 661 billion of economic losses were recorded due to earthquakes. Currently, there is no clear precursor to forecast earthquakes. However, numerous investigations have attempted to find precursor proxies based on Land Surface Temperature (LST) anomalies. In this study, a big database collected from GOES/ABI instrument during the full year 2020 has been used to calculate the LST anomalies in the earthquakes zones. A total of 1350 earthquakes of Mw ≥ 4 were studied in 2020. Two methods commonly used in the literature, the interquartile method, and the standard deviation of the time series, have been applied to detect LST anomalies. The confusion matrix, some figures of merit, and the receiver operating characteristic curve have been used to evaluate and enhance the performance of the methods and choose the optimum decision threshold. A positive anomaly is usually found before the earthquakes, followed by an LST decrease after the event.

Vegetation canopy height (CH) is one of the important remote-sensing parameters related to forests’ structure, and it can be related to the biomass and the carbon stock. Global navigation satellite system-reflectometry (GNSS-R) has proved capable to retrieve vegetation information at a moderate resolution from space (20–65 km) using L1 C/A signals. In this study, data retrieved by the airborne microwave interferometric reflectometer (MIR) GNSS-R instrument at L1 and L5 are compared to the Global Forest CH product, with a spatial resolution of 30 m. This work analyzes the waveforms (WFs) measured at both bands, and the correlation of the waveform width and the reflectivity values to the CH product. A neural network algorithm is used for the retrieval, showing that the combination of the reflectivity and the waveform width allows to estimate the CH information at a very high resolution, with a root-mean-square error (RMSE) of 4.25 and 4.07 m at L1 and L5, respectively, which is an error about 14% of the actual CH.

The ability to enhance the spatial resolution of measurements collected by a conical-scanning microwave radiometer (MWR) is discussed in terms of noise amplification and improvement of the spatial resolution. Simulated (and actual) brightness temperature profiles are analyzed at variance of different intrinsic spatial resolutions and adjacent beams overlapping modeling a simplified 1-D measurement configuration (MC). The actual measurements refer to Special Sensor Microwave Imager (SSM/I) data collected using the 19.35 and the 37.00 GHz channels that match the simulated configurations. The reconstruction of the brightness profile at enhanced spatial resolution is performed using an iterative gradient method which allows a fine tuning of the level of regularization. Objective metrics are introduced to quantify the enhancement of the spatial resolution and noise amplification. Numerical experiments, performed using the simplified 1-D MC, show that the regularized deconvolution results in negligible advantages when dealing with low-overlapping/fine-spatial-resolution configurations. Regularization is a mandatory step when addressing the high-overlapping/low-spatial-resolution case and the spatial resolution can be enhanced up to 2.34 with a noise amplification equal to 1.56. A more stringent requirement on the noise amplification (up to 0.6) results in an improvement of the spatial resolution up to 1.64.

Radio Frequency Interference (RFI) is an increasing problem particularly for Earth Observation using Microwave Radiometry. RFI has been observed, for example, at L-band by the ESA’s SMOS (Soil Moisture and Ocean Salinity) Earth Explorer and by NASA’s SMAP (Soil Moisture Active Passive) and Aquarius missions, as well as at C-band by AMSR-E and AMRS-2; and at 10.7 GHz and 18.7 GHz by AMSR-E, AMRS-2, WindSat and GMI [1], [2]. Therefore, systems dedicated to interference detection and removal of contaminated measurements are nowadays a must in order to improve the radiometric accuracy and reduce the loss of spatial coverage caused by interference. In this work, the feasibility of using the Empirical Mode Decomposition (EMD) technique for RFI mitigation is explored. The EMD, also known as Hilbert-Huang Transform (HHT), is an algorithm that decomposes the signal into Intrinsic Mode Functions (IMF). The achieved performance is analyzed, and the opportunities and caveats that this type of methods present are described. EMD is found to be a practical RFI mitigation method, albeit presenting some limitations, and a considerable complexity. Nevertheless, in some conditions, EMD exhibits a better performance than other commonly used methods (such as frequency binning). In particular, it has been found that EMD performs well for RFI affecting the < 25% lower part of the Intermediate Frequency (IF) bandwidth.

The calibration strategy for synthetic aperture interferometric radiometers based on noise injection has been successfully demonstrated in the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument onboard the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA). With the emerging demands of increasing both array size and frequency bands, the internal calibration hardware becomes more difficult to implement. Although several external calibration methods have been proposed, the so-called phase ambiguity problem was not carefully considered. In this article, a novel calibration strategy for both phase and amplitude calibrations based on redundant space calibration is proposed, which utilizes the unique structure of equispaced circular array and rotational sampling strategy. The original irregular phase ambiguity degenerates to the fixed$\pi $-ambiguity, where only two possible solutions to phases are introduced. Both phase and amplitude of visibility can be simultaneously calibrated by the proposed strategy, and no cooperative calibration target is needed.

In the theoretical part of this work, a calibration strategy for both phase and amplitude calibration of rotating equispaced circular array based on redundant space calibration was introduced. It avoids the challenging implementation of conventional noise-injection networks, especially for a large-scale array, by using the strong self-consistency accomplished by array rotation. This study presents comprehensive simulation results of the proposed calibration strategy, where calibration residuals and image reconstruction errors are evaluated. The phase calibration shows outstanding performance, while the amplitude calibration is found to be biased due to the logarithms used to linearize the system of calibration equations, and the resulting image reconstruction bias is scene-dependent. A bias correction method is proposed accordingly, which requires ana prioriregional brightness temperature within the observation scene. The performance of both phase and amplitude calibration take advantage of increasing the number of elements, which promises the system scalability for high spatial resolution applications.

Soil Moisture and Ocean Salinity mapping by Earth observation satellites has contributed significantly toward a better understanding of the Earth system, such as its hydrosphere or climate. Nevertheless, an increased spatial resolution below 10 km with a radiometric resolution in the range of 2 K–3 K of radiometric data could yield a more complete picture of global hydrological processes and climate change. Operational radiometers, such as SMOS, have already approached prohibitive sizes for spacecraft due to the required large antenna apertures. Therefore, radiometer concepts based on a large number of satellites flying in close proximity (swarms) have been proposed as a possible solution. This article investigates the orbit mechanics of placing a satellite swarm-based motion induced synthetic aperture radiometer (MISAR) in low Earth orbit for Earth observation applications. The aperture synthesis antenna array is formed by a large number of individual antennas on autonomously controlled nanosatellites (deputies) and a correlator antenna in the Y-configuration carried by a chief satellite. The proposed design methodology is based on the optimization of satellite positions within a plane and the subsequent translation of coordinates into initial conditions for general circular orbits (GCOs). This enables a more computationally efficient orbit optimization and ensures the time invariance of the antenna array response. Based on this methodology, simulations have been performed with swarms consisting of up to 96 satellites. Simulations show that the spatial resolution of an aperture synthesis radiometer can be increased to less than 10 km for applications where the requirements on radiometric sensitivity are more relaxed ($\Delta T\sim 3$K).

An enhanced spatial resolution brightness temperature product is proposed for future conical scan microwave radiometers. The technique is developed for Copernicus Imaging Microwave Radiometer (CIMR) measurements that are simulated using the CIMR antenna pattern at the L-band and the measurement geometry proposed in the Phase A study led by Airbus. An inverse antenna pattern reconstruction method is proposed. Reconstructions are obtained using two CIMR configurations, namely, using measurements collected at L-band by the forward (FWD) scans only, and combining forward and backward (FWD+BWD) scans. Two spatial grids are adopted, namely,$3 \mathrm {\,\,km} \times 3 \mathrm {\,\,km}$and$36 \mathrm {\,\,km} \times 36 \mathrm {\,\,km}$. Simulation results, referred to synthetic and realistic reference brightness fields, demonstrate the soundness of the proposed scheme that provides brightness temperature fields reconstructed at a spatial resolution up to ~1.9 times finer than the measured field when using the FWD+BWD combination.

Knowledge about sea ice concentration and extent in polar regions is of great interest both for economic interests, and as a proxy of the climate change. Retrieved maps are based on data from microwave radiometers, which are currently provided by large satellite missions. Nowadays, CubeSats have proven to be a cost-effective alternative. Due to their low cost, they can be launched in large constellations to obtain high spatial coverage and daily revisit. This study presents a neural network approach to generate sea ice concentration and sea ice extension maps using the L-band microwave radiometer, and the GNSS-Reflectometer data from the FMPL-2 instrument onboard3Cat-5/A, one of the two CubeSats of the FSSCat mission. The results obtained during the first 2 months of the mission are presented.

Several factors may induce perturbations on the ionospheric plasma, changing its average electron density and creating small-scale irregularities, changing its shape and altitude. Solar irradiance and space weather are some of the main factors affecting the ionosphere. They produce a seasonal and daily dependence, modulated by the solar cycle, with more ionospheric activity during periods of higher solar activity. Recent studies shows that another source of perturbations for the ionosphere may be related to internal Earth parameters as seismic activity, in particular, earthquakes. In the period before an earthquake, rocks in the lithosphere are subjected to pressures and movements that may create variations of electromagnetic fields and low frequency waves interacting with the ionosphere. In this work, the ionospheric scintillation intensity index or S4 is estimated from GNSS-R data collected by NASA CYGNSS, and it is correlated with earthquakes events in 2020. Furthermore, it is compared with plasma fluctuation indices measured by ESA Swarm satellites. Two earthquakes in 2020 with magnitudes larger than 7 in the central America region are shown in this work.

The Flexible Microwave Payload -2 is the microwave remote sensing payload of the FSSCat mission. The instrument is the outcome of years of work of the Universitat Politécnica de Catalunya Passive Remote Sensing Laboratory, and the NanoSat-Lab. The FSSCat mission was launched on board the Vega VV16, on September the 3rd, 2020. The instrument was executed for the very first time on September the 16th, 2020, and it was commissioned less than two weeks later. This extended abstract presents the geo-located FMPL-2 measurements, which consist of a Global Navigation Satellite System - Reflectometer and an L-band radiometer. The performance of the instrument and preliminary level 1C results are presented, showing that CubeSats can to perform passive microwave remote sensing scientific missions.

The Microwave Interferometric Reflectometer (MIR) is an airborne GNSS-R instrument developed by Universitat Politècnica de Catalunya. In 2018, it was flown twice over the agricultural Yanco area, New South Wales, Australia, once after a very dry period, and a further time the day after a strong rain event. This rain event resulted in many crop fields being entirely flooded, producing a saturation in the GNSS-R reflectivity value. In this work, the received data set is processed to identify the optimum integration time with the goal to minimize pixel blurring. This issue is assessed for airborne conditions, and then extra-polated to the spaceborne case. The presented results show that the blurring of the GNSS waveform is produced even from an airborne sensor with short integration times. Following the determination of an optimal integration time for the platform in use, the surface roughness term in the reflectivity equation can be isolated due to the signal saturation during very wet surface conditions. The final results from the two channels (L1 C/A and L5) are subsequently presented. In this case, it is shown that most reflectivity variations in GNSS-R measurements are linked to surface roughness and Speckle noise fluctuations rather than soil moisture changes.

A modification to the extended CLEAN deconvolution method for passive microwave interferometric radiometers is presented to account for the interferometer beam patterns that vary depending on the source position within the interferometer field of view. This method is developed for the newly proposed multisatellite rotating microwave interferometric radiometer concept for geostationary atmospheric sounding, which is found to have a spatially varying beam pattern. The proposed method is implemented by the piecewise application of Fast Fourier Transform (FFT)-based convolution, i.e., the image is divided into discrete segments, where the beam pattern is assumed to be constant within each segment. This approach allows the proposed method to exploit the speed advantage of the FFT. Applying this method to the proposed multisatellite interferometer shows a twofold improvement in the radiometric accuracy of the restored brightness temperature map, as compared with the constant beam pattern CLEAN.

The ionosphere impacts radio-wave propagation, notably up to a few GHz. The main applications impacted by the ionosphere are GNSS positioning and timing, Earth Observations (especially low frequency SAR missions e.g. BIOMASS, and GNSS-R), and Space Weather. While most effects can be compensated by using dual-frequency receivers and circular polarization antennas, ionospheric scintillation (rapid intensity and phase fluctuations) cannot. Climatological models for the mean stable part of the electron density in the ionospheric layers (e.g. IRI or NeQuick) or for the magnetic field (e.g. WMM) have significantly improved in the past years. However, models of the inhomogeneous part, responsible for scintillation, can be improved, since they are based on relatively old data (e.g. WBMOD), or climatological inputs are limited to properly characterize all latitudes and solar conditions (e.g. GISM or WAM). This study first assesses the goodness of GISM, the model adopted by the ITU-R, by comparing GISM predictions and measured scintillation data. Then, the impact of measured intensity and phase scintillation on TDS-1 GNSS-R data is illustrated.

Attitude determination and control systems (ADCS) are critical in many satellite missions, especially when high pointing accuracy is needed, such as in optical imagers. Current actuators used to control the platform's attitude, such as reaction wheels or magnetorquers, have some limitations, inducing some jitter, which is crucial in small satellites. This jitter induces the image blurring. This work analyzes the impact of actuator's jitter, and then a deblurring technique to minimize and correct the distortion produced is studied. Two points are addressed to restore the blurred images. First, the data coming from the inertial sensors embarked on the satellite to infer the movement of the camera is used. Secondly, a deblurring technique for non-constant blurring over an image is applied.

As compared to the using L1C/A signals, L5/E5a Global Navigation Satellite System - Reflectometry (GNSS-R), gives improved resolution over the Earth's surface due to the sharper auto-correlation function. Furthermore, the larger transmitted power (+3dB with respect to L1 C/A), and correlation gain (+40dB) allows the reception of weaker reflected signals. If high directivity antennas are used, very short incoherent integration times are needed to have enough signal-to-noise (SNR) ratios, allowing the reception of multiple specular reflection points such as crest of consecutive waves without the blurring induced by long incoherent integration times. This study presents for the first time experimental evidence of the wind and swell waves signatures in the GNSS-R waveforms, and compares them with models.

Global Navigation Satellite Systems Reflected (GNSS-R) signals exhibit an incoherent and a coherent components [1], [2]. Current models assume that one or the other are dominant, and the calibration, and geophysical parameter retrieval (eg. wind speed, soil moisture ...) are developed accordingly. Even the presence itself of the coherent component of a GNSS reflected signal has been a matter of discussion in the last years. In this work, the method used in [3] to separate the leakage of the direct signal from the reflected one is applied to a set of GNSS signals reflected collected over the ocean by the MIR [4], [5], an airborne dual-band (L1/E1 and L5/E5a), multi-constellation (GPS and Galileo) GNSS-R instrument with two 19-elements array with 4 beam-steered each. The results presented demonstrate the feasibility of the proposed technique to untangle the coherent and incoherent components in GNSS reflected signals. This technique allows the processing of these components separately, which will increase the calibration accuracy (as today both are mixed together), and allows high resolution applications since the spatial resolution of the coherent component is determined by the size of the first Fresnel zone [6] (300-500 meters from a LEO satellite), and not by the size of the glistening zone (~25 km from a LEO satellite).

Global Navigation Satellite System (GNSS) signals are used in Earth Observation for Radio Occultation and Reflectometry. The increasing effects of Radio-Frequency Interferences (RFI) on the performance of these receivers and navigation have suddenly sparked serious concerns due to their proliferation. Detection and mitigation of RFI heavily relies on the nature and location of the interfering sources. In some cases, null-steering or shielding can be used to mitigate RFI effects. In this work, a system to detect and locate RFI sources is presented, including signal classification and recording for countermeasure-related decision-making.

The relative phase and amplitude calibration between individual receiving elements are one of the key challenges in interferometric microwave radiometry. For monolithic interferometers, for example the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) on board the Soil Moisture and Ocean Salinity (SMOS) mission, the calibration of these two parameters is accomplished by correlated noise injection, where a noise signal from a central noise source is distributed to multiple elements in phase, and any measured phase and amplitude differences can be measured and compensated. As new multisatellite interferometers are being proposed, a new strategy capable of calibrating these errors between the free-flying antennas as well as any antenna position errors is required. In this article, a new calibration scheme is proposed which uses a set of microwave beacons in place of the central noise source, placed at known locations within the interferometer's field of view. The visibility function produced by these point-sources can be precalculated, and any errors between the calculated and the measured visibility samples can be attributed to the errors to be determined. Since the phase of the measured visibility is a function of phase and antenna position errors, this technique is capable of calibrating these two parameters simultaneously. Calibration equations for far- and near-field beacons are presented. Using these expressions, five interferometric calibration routines are proposed and examined for geostationary formation flight microwave radiometers. Although this technique is ideal for multisatellite interferometers with variable antenna positions, it is also applicable to monolithic interferometers that can undergo substantial array deformation.

In this study, the ability of GNSS-R technique to observe and track hurricane is investigated from the CYGNSS mission, as the specular reflection points tracks pass through the eye of Hurricane Irma. The clear variations of the CYGNSS observables, including the Normalized Bistatic Radar Cross Section (NBRCS), the Leading Edge Slope (LES), the Signal-to-Noise ratio (SNR), and the derived wind speed, are examined. CYGNSS-derived wind speeds are compared to other satellite missions, including ASCAT, WindSat, and SMAP. CYGNSS-derived wind speeds exhibit a similar behaviour than the collocated ASCAT, WindSat, and SMAP over the hurricane eye, but are underestimated under high wind conditions.

Global Navigation Satellite System Reflectometry (GNSS-R) uses the GNSS reflected signals to study parameters of the Earth's surface such as ocean surface height, wind speed, soil moisture, sea surface target detection. In this paper fourteen DDMs (Delay Doppler Maps) of TechDemoSat-1 (TDS-1) containing anomalous artefacts are presented and analyzed. Anomalous artefacts are not caused by the reflection from Earth surface targets, occultation, nor the leakages of direct signals, but likely - according to their delays- from reflection of targets above the Earth's surface (either airborne or spaceborne).

Thanks to the successful operations of the UK TDS-1 and NASA CYGNSS GNSS-R missions, a wealth of Delay-Doppler Maps (DDM) are being measured from the ocean, but also from land reflections. Using the land reflected DDM, several studies are being conducted to retrieve the land geophysical parameters, such as soil moisture, vegetation depth, and biomass. Although they have shown the dependence of the land geophysical parameters on the DDM, it is also shown that many other parameters impact the DDM. This work presents the impacts of some parameters on the DDM. For the systematical and efficient study, an E2E simulator is used. The simulator generates the synthesized DDM reflected over land varying the input parameters, which are the specular point position on the Earth, the elevation angle at the specular points, soil moisture, etc. From the simulation results, the relation between the input parameters and the DDM is individually analyzed, providing the clue to the retrieval algorithm of the geophysical parameters.

As the TDS-1 and CYGNSS spaceborne GNSS-R missions progress, a large number of Delay-Doppler Maps (DDM) is being collected, from the land scattered as well as from the ocean. Based on those data, the feasibility study on the retrieval of land geophysical parameters such as soil moisture and vegetation is being studied. This work presents the E2E simulator that generates the synthesized DDM reflected over land. For the efficient development, the existing simulator for ocean scattering has been upgraded to accommodate the specific functionalities for land scattering: topography, surface roughness, vegetation effects, in addition to surface soil moisture, obviously. The developed end-to-end (E2E) simulator is used to conceive the retrieval algorithms and assess their performance. In this work, the upgraded items are described and illustrated with some simulation results.

The characterization of the ionosphere and its impact on the propagation of radio-wave signals has received an increasing interest for satellite communications, Global Navigation Satellite Systems (GNSS) applications (i.e. navigation and timing), and Earth Observation (EO) missions, especially low frequency SAR missions and GNSS-Reflectometry (GNSS-R). Although the main climatological models for the mean stable part of the electron density in the ionospheric layers (e.g. IRI or NeQuick) or for the magnetic field (e.g. WMM) have been significantly improved in the past years, the inhomogeneous part, responsible for scintillation effects, can still be significantly improved, since models are based on relatively old data (e.g. WBMOD), or the climatological inputs are limited to properly characterize all latitudes and solar conditions (e.g. GISM or WAM). ESA's CLIM IONO study aims to use the experimental observations of the ionosphere collected in the past years to assess the performance of climatological ionosphere models, with the focus on scintillation models, in order to evaluate their ability to properly support future needs, to identify weak areas if any, to propose recommendations for improvements and to implement these improvements whenever possible in existing models. This work focuses on the capabilities of GNSS-R techniques to characterize ionospheric scintillation, notably at low and high latitudes.

The potential of GNSS-R techniques to estimate land surface parameters such as Soil Moisture (SM) is experimentally studied using 2014-2017 global data from the UK TechDemoSat-1 (TDS-1) mission. The approach is based on the analysis of the sensitivity to Soil Moisture of different observables extracted from the Delay Doppler Maps (DDM) computed by the SGR-ReSI instrument using the L1 (1575.42 MHz) left-hand circularly-polarized (LHCP) reflected signals emitted by navigation satellites. After quality-filtering the data (spacecraft not `in eclipse' and the direct signal not present in the DDM), topography filtering the data, correction for background noise, antenna pattern gain, different distance propagation factors, and vegetation attenuation, the sensitivity of different GNSS-R observables to SM and its dependence with incidence angle is analyzed.

The3Cat-3/MOTS mission is a joint initiative between the Institut Cartogràfic i Geològic de Catalunya (ICGC) and the Universitat Politècnica de Catalunya-BarcelonaTech (UPC) to foster new and innovative technologies on Earth Observation (EO) based on the data fusion of Global Navigation Satellite Systems Reflectometry (GNSS-R) and optical payloads on a 6U CubeSat platform. The final objective of the mission is to provide soil moisture mapping through the GNSS-R payload and improve its resolution by data fusion with the multi-spectral optical data acquired. This technique has been successfully applied to SMOS, but never performed from a 6U CubeSat carrying both payloads. An airborne optical and GNSS-R field experiment has been carried out to test/develop the algorithm and to analyze the results both separately (GNSS-R + optical data) and as a soil moisture product, once performed the data fusion.

This work is part of “Operational Network of Individual Observation Nodes” (ONION). ONION is an H2020 project devoted to identify solutions and to satisfy emerging needs of the European Earth Observation (EO) market. In this regard, this work presents a review and analysis of the potential payloads and next generation of sensors in order to cover the measurements gaps of the top ten use cases of the European EO infrastructure. For each use case the potential instruments to support stakeholder requirements are identified, pointing out the aspects in which they represent an innovation with respect to existing technological solutions. This identification of instruments is based on existing, operational, under development, and demonstration missions. The capability of the instrument technologies is evaluated according to the trends in the design for small EO satellites (payload mass <; 500 kg). This work concludes with a set the potential instruments to be possibly developed as part of the future European space infrastructure, proposing an integrated set of instruments and measurements to optimize the performances, simplifying the implementation, and reducing the costs.

Global Navigation Satellite Systems - Reflectometry (GNSS-R) has shown his potential for remote sensing. Since new wider band signals are being broadcasted, and new systems are becoming available, a performance comparison in fair conditions between signals and system is required. For this purpose, the Universitat Politecnica de Catalunya has been developing the MIR instrument, an airborne GNSS reflec-to meter that mimics PARIS-IOD, and that also aims to better understand some GNSS-R techniques, the RFI analysis and mitigation, and the use of beamforming techniques to improve the GNSS-R capabilities. This work presents the advances in the instrument, the end-to-end tests, and the field campaign being planned in Australia for Spring, 2018.

In order to provide high resolution soil moisture maps, the Institut Cartografic i Geológic de Catalunya (ICGC) in colab-oration with Universitat Politecnica de Catalunya are planing to deploy the3Cat-3 picosatellite, which aims to estimate soil moisture from space using Global Navigation Satellite Systems - Reflectometry (GNSS-R) and to downscale it using data fusion with a multi-spectral camera. As a proof of concept, a field campaign is being carried out in Lleida, Catalunya. MALYGNSS is a GNSS reflectometer flying as an opportunity sensor that will validate the main reflectometer of the project: the CORTO instrument.

The maximum coherent integration time of GNSS reflected (GNSS-R) signals over sea depends on the sea state, as well as on the geometry formed by the receiver, the GNSS satellite and the reflection point. In this paper, real data obtained with a dedicated airborne instrument named MALYGNSS (Multi-band Airborne L-Band reflectometrY with GNSS) is used to acquire GPS L1 C/A and L2C, and Galileo E1OS signals. The direct signals are used as a reference to detect any phase shift due to data bits changes and the presence of a residual Doppler frequency. These phase transitions are removed in the reflected signals, and coherent correlations of different lengths are performed in order to study sea correlation time.

Radio-Frequency Interference (RFI) is one of the most concerning topics in Global Navigation Satellite Systems (GNSS) and GNSS - Reflectometry (GNSS-R) because any undesired signal present at the antenna can corrupt the received signal and the eventual geophysical measurements. The purpose of this paper is two-fold. First, an RFI analysis is performed to the raw data obtained from an airborne dual-band GNSS reflectometer. Finally, the Front-End GNSS Interference eXcisor (FENIX) mitigation algorithm is applied to the raw data, and then the Signal-to-Noise Ratio (SNR) improvement at the Delay-Doppler Map (DDM) is obtained. From the analysis of one of the datasets, two RFI signals were detected and characterized. Moreover, FENIX output signal was revealed to be much cleaner than before. The mean SNR improvement with coherent DDMs of 1 ms is 0.72 dB, whereas the SNR improvement increases to 1.49 dB when considering 50 incoherent averages. This improvement represents a reduction in the geophysical parameter estimation uncertainty.

The impact of Radio Frequency Interference (RFI) is a very serious problem for spaceborne microwave radiometry. Many Soil Moisture Ocean Salinity (SMOS) images show serious contamination by the RFI. SMOS is even more impacted by the RFI than real aperture case because the grating lobes are usually higher in Synthetic Aperture Interferometric Radiometer (SAIR) compared to real aperture one. RFI effects should properly be mitigated or filtered out to retrieve the geophysical parameters from SMOS measurements. This work presents a feasibility study of RFI mitigation/filtering for SAIRs. Instead of dealing with brightness temperature image directly, RFI filtering of the subspace of covariance matrix is introduced.

This work reviews and analyses potentially relevant technologies to ensure that the gaps and stakeholder needs for sea ice products are covered. Each variable related to sea ice that presenting gaps using the European EO infrastructure on the horizon (2020-2030) is revised according the stakeholder requirements, together with the feasibility of deploying available technologies on small satellites. A survey of instruments oriented towards sea ice observations in the past and current is presented. Based on this survey technological capabilities in terms of the spatial resolution, swath, mass, power, and data rate are obtained. In order to identify the technologies, numerical scores are assigned based on instrument capabilities. This works concludes with a set of the technologies compatible with small platforms, with the objective to complement the sea ice data products of Copernicus Services.

Global Navigation Satellite Systems - Reflectometry (GNSS-R) has opened promising results for remote sensing applications. The broadcast of new signals with wider bandwidth provides an opportunity to increase the performance of GNSS reflectometry applications. The Microwave Interferometric Reflectometer (MIR) is an instrument being developed to compare different GNSS-R techniques, namely the conventional and interferometric ones, and assess the capabilities of these new signals and bands of the GPS and Galileo systems. This work describes the tests to validate the beamforming system.

The demonstration of the feasibility of navigation signals signals for remote sensing has lead to a significant increase of new GNSS-R instruments in the recent years. Despite of the type instrument, the observables are based on the cross-correlations of the received GNSS signals. Most of these instruments combine the signals received by multiple chains, in such a way that they need a proper calibration. This work proposes a calibration procedure for GNSS-R instruments by using a calibration signal with similar statistics to the GNSS signals. The method is tested and validated with the Microwave Interferometric Reflectometer (MIR) instrument, which contains 152 chains. The test results will be presented at the conference.

Radio-Frequency Interference (RFI) is a growing problem for applications based on the Global Navigation Satellite Systems (GNSS), including Earth observation using GNSS - Reflectometry (GNSS-R). Nowadays, many efforts are being concentrated to develop RFI signal detectors with high sensitivity, which can help to control the proliferation of RFI generators or jammers. This work aims at designing and testing an instrument capable of detecting and localizing RFI signals at GNSS bands using a microwave radiometer architecture, and a combination of statistical and time-frequency digital detection techniques. The instrument has been tested using different kinds of RFI signals, and its performance has been evaluated as a function of the RFI power. A sensitivity of -135 dBm for continuous wave and chirp signals is reported.

Ships and ice monitoring is of key importance in numerous applications, such as maritime traffic control, prevention of illegal activities, climate change studies, and maritime security. In this work, the feasibility of near real-time ocean target detection from a constellation of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) images is demonstrated by addressing the two following points: 1) simulation of the revisit time allowed by constellations of GNSS-R instruments; 2) derivation and implementation of an ocean target detector aimed at identifying inhomogeneous features inside the delay-Doppler map. The revisit time is computed by simulating a realistic mission as a function of the constellation size and the number of receiving channels of the GNSS-R instrument. The proposed ocean target detection algorithm consists of four steps — pre-processing, pre-screening, selection, and geolocation — and is validated using actual U. K. TechDemoSat-1 data.

This work shows a technique to estimate the vegetation opacity and infer the vegetation water content using a single GPS receiver located under the vegetation layer being analyzed. It is based on the measurement of the received signal power when the GPS satellite is at the zenith, and when the GPS satellite is with an elevation of 30 degrees. Assuming a horizontally stratified vegetation layer, the attenuation on the GPS signal due to vegetation doubles at 30° elevation angle compared to the zenith. This attenuation is directly related to the vegetation opacity. Then, the vegetation opacity is related to the vegetation water content by a linear parameter. Initial results relating the measured GPS signal power to canopy parameters obtained from hemispheric photos are shown.

The GNSS rEflectometry, Radio Occultation and Scatterometry onboard the International Space Station (GEROS-ISS) is an innovative experiment for climate research, proposed in 2011 within a call of the European Space Agency (ESA) for installation at the ISS. This international proposal was the only one selected for further studies by ESA out of ~25 submitted ones. In this work, an updated assessment of the instrument performance for the near-nadir altimetry (GNSS-R) mode and scatterometry is assessed, including the effect of the inter-modulation signals, and the expected degradation due to presence of radio-frequency interference coming from DME/TACAN systems. These results correspond to the study lead by Airbus Defence and Space-Spain, one of the two parallel Phase A studies conducted by ESA.

Global Navigation Satellite Systems-Reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multi-static radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from a ground-based and airborne experiments, but studies using space-borne data are still preliminary. This work presents a sensitivity study of Using TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e. vegetation covers). Despite the scattering in the data, which can be attributed to the temporal and spatial (footprint size) collocation mismatch with the SMOS and MODIS NDVI data, and errors in the land use data preliminary results show a good correlation with soil moisture.

Global Navigation Satellite Systems Reflectometry (GNSSR) is now being recognized as a powerfull tool for remote sensing. With the addition of new frequency bands and codes, it is possible to increase the resolution and accuracy of the measurements. GPS L5 and Galileo E5 bands are becoming popular because of the open codes, with wider bandwidths than the L1 band ones. However, these bands are shared with two radio navigation systems (DME and TACAN) that transmit with high powers and might interfere them. The use of mitigation techniques may affect the power of the received signal, which will affect the GNSS-R observables. This work presents several the mitigation techniques, and evaluates the performance and impact of the selected ones for ESA's GEROS experiment onboard the International Space Station.

This work presents an improvement of the P2EPS end-to-end simulator to assess the performances of Global Navigation Satellite System Reflectometry (GNSS-R) space missions over land. Beyond the single specular reflection model, topography effects are included. In order to avoid the computational burden of facet approach based on the bi-static radar model, the Phong reflection model is employed. By calculating the delay, Doppler frequency, and relative intensity of scattered points, the topography effects can be accounted for as a sort of impulse response in the delay, and Doppler domains to be convolved with the Woodward Ambiguity function.

The GNSS rEflectometry, Radio Occultation and Scatterometry onboard the International Space Station (GEROS-ISS) experiment consists of the installation of a GNSS reflectometry (GNSS-R) instrument on the International Space Station (ISS). Due to the complex structure of ISS, the GEROS-ISS instrument suffers from multipath effects. The collected signals are not only from received directly, but also after multiple reflections in the ISS structure. This work analyzes the multipath effect of the GEROS-ISS instrument based on the ISS structure. Using the ray tracing simulation, all rays reaching the instrument after one or two reflections are computed, as well as the corresponding additional delays. This information, together with the direction of arrival to the antenna arrays (up and down-looking), and the co- and cross-polar antenna patterns is used to assess the impact of multipath on the waveforms are demonstrated.

This work presents the first Delay Doppler Maps (DDMs) obtained with the Microwave Interferometric Reflectometer (MIR) airborne instrument. MIR is a GNSS Reflectometer (GNSS-R) which uses the conventional (cGNSS-R) and interferometric (iGNSS-R) techniques for ocean and land observation. It computes real-time sample-to-sample complex DDMs with averaging and alignment, of up to 4 simultaneous GPS/Galileo satellites at the L1/E1, and L5/E5a bands. Satellites are tracked with high directivity antennas with beam steering. The MIR instrument is designed to validate and compare both GNSS-R techniques with the new available signals, with special focus in the GEROS-ISS payload, and to contribute to the development of geophysical retrieval algorithms.

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 European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, and multiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.

This work presents two field campaigns performed between December 2014 and June 2015 in order to better understand the behavior of Global Navigation Satellite Systems (GNSS) reflected signals over land. The instruments used in both field campaigns are briefly introduced. One of them is focused on circular polarization, whereas the other is focused on linear polarization (horizontal and vertical). In one field experiment there is evidence of multipath due to the antenna performance. A method to mitigate it is proposed in this work. Finally, some preliminary soil moisture estimations using vertical polarization are shown.

The GNSS rEflectometry, Radio Occultation and Scatterometry onboard International Space Station (GEROS-ISS) is an innovative experiment for climate research, proposed in 2011 within a call of the European Space Agency (ESA) for installation at the ISS. This international proposal was the only one selected for further studies by ESA out of ~25 submitted ones. In this work, the assessment of the instrument performance for the near-nadir altimetry (GNSS-R) mode is assessed, including the effects of multi-path in the ISS structure, the electromagnetic-bias, and the orbital height decay. In the absence of ionospheric scintillations, the altimetry rms error is20 dB at equatorial regions, mainly after sunset, which will seriously degrade the altimetry and the scatterometry performances of the instrument.

For a given geometry, the coherence time of a GNSS-R waveform can be initially related to the significant wave height. However, when the coherence time is analyzed, several issues shall be considered, such as the geometry (i.e altitude, elevation angle). This work presents a review of the coherence time and its dependence on the geometry. In addition, the impact that the SWH has on both the coherence time and elevation angles is analyzed. Real data from different scenarios (spaceborne, airborne, and ground based) are used in this study.

The effectiveness of incoherent averaging depends on the level of correlation between consecutive waveforms, which can vary with the geometry and with the sea state conditions. In addition it is also dependent on the lag position, since the level of correlation is not the same for all the lags. An initial estimation of the lag correlation can be done by means the ratio (R) between the actual number of incoherent averages and the effective number of incoherent averages. This work is structured in two parts: In the first part the concept of using of the ratio R as a new observable to estimate the significant wave height is detailed. In the second part, data from the TIGRIS experiment is used in order to relate the R with the significant wave height, comparing its performance with the performance obtained with the coherence time.

The MIR (Microwave Interferometric Reflectometer) is a new dual frequency Global Navigation Satellite Systems Reflectometry (GNSS-R) instrument that implements conventional and interferometric reflectometry, both with GPS and Galileo signals. This paper presents the instrument development progress, mainly in the control part, where a methodology to determine how much the platform attitude will affect the beam steering and a satellite selection algorithm have been developed.

In the SMOS measurements, the negative effect of Radio-Frequency Interference (RFI) is clearly present, deteriorating the Brightness Temperature (BT) images. RFI sources have to be monitored and accurately geolocated in order to improve the quality of geophysical parameter retrieval from the SMOS BT image, and eventually develop algorithm to cancel them. This paper present a case study of SMOS RFI source detection and geolocation based on MUSIC (MUltiple SIgnal Classification) algorithm. Thanks to the high angular/spatial resolution of MUSIC algorithm, the RFI sources densely populated in East Asia can be separately geolocated, which is difficult using SMOS standard brightness temperature images.

This work shows a state-of-the-art GNSS reflectometry end-to-end performance simulator, selected for the ESA's GNSS rEflectometry, Radio Occultation and Scatterometry onboard International Space Station (GEROS-ISS). For the efficient development process, the PAU/PARIS End-to-end Performance Simulator (P2EPS) are used as main building blocks for the GEROS-Simulator. To accommodate the GEROS specific situation of platform and instrument, P2EPS is modified. Additionally, several considerations in spaceborne GNSS-R techniques are newly updated in GEROS-SIM, improving the performance in terms of accuracy and completeness. GEROS-SIM will be delivered as a web application, i.e., executable via web browser connecting GEROS-SIM webpage hosted by UPC-BarcelonaTech.

Radio-frequency interference (RFI) seriously affects the retrieval of geophysical parameters from the measurements of microwave radiometers. An accurate geolocation of the RFI is crucial to effectively switch off illegal transmitters. In this letter, a new RFI localization method is proposed to improve the achievable angular resolution by using beamforming and direction-of-arrival (DOA) estimation techniques. The proposed RFI localization techniques can be employed in synthetic aperture interferometric radiometers, such as the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. Two DOA estimation techniques are tested for the RFI localization: Capon and MUSIC. The feasibility of these methods is demonstrated with SMOS data. In the test results, the MUSIC beamforming shows a better performance of RFI localization than the SMOS Fourier imaging and the Capon, in terms of accuracy and resolution.

Since 1993, when the European Space Agency (ESA) proposed the use of Global Navigation Satellite Systems reflected signals for sea mesoscale altimetry, a wide range of applications have appeared. This paper focuses on the retrieval of significant wave height (SWH) and the mean sea surface level (MSSL) from a ground-based experiment using the interference pattern technique (IPT). Two different observables on the IPT are analyzed: the oscillation frequency and the angle where coherency is lost. The point where coherency in the reflection process is lost can be related to the Rayleigh criterion for smooth surfaces and helps to determine the SWH. Spectral analysis on the interference pattern helps to determine the MSSL. A three-month field campaign was performed on the “Pont del Petroli” pier, Badalona, Spain, to see how the reflected GNSS signals were affected by coastal sea state and check previous assumptions. Results from this field experiment are shown, confirming that the SWH can be retrieved with accuracy of 6 cm and the MSSL with 4 cm. Estimations of both parameters are obtained every 30 min approximately.

Global Navigation Satellite Systems (GNSS)-Reflectometry (GNSS-R) has proved to be a useful technique for the estimation of Soil Moisture (SM). In the past 10 years, different techniques such as the Interference Pattern Technique (IPT), the Interferometric Complex Field (ICF) or power measurements of direct and reflected GNSS signals have been used. This work presents a reflectometer concept that can be used for air-borne, Unmanned Aerial Vehicle (UAV), car-borne, and ground-based measurements. It also presents the hardware implementation and the data acquisition scheme. An algorithm for the estimation of the reflectivity of the surface under observation has been developed and compared to concurrent radiometric measurements. Initial results from an airborne field experiment have shown a good correlation between both data sets.

Since 2003 several field experiments using Global Navigation Satellite Systems (GNSS)-Reflectometry (GNSS-R) have demonstrated the feasibility of retrieving Soil Moisture (SM) from GNSS-R observations. Different techniques such as the power difference between direct and reflected signals, the Signal to Noise Ratio (SNR)-analysis method, the Interference Pattern Technique (IPT) or the Interferometric Complex Field (ICF) have been used. The conventional IPT was first proposed in 2008, and consisted on forcing a single multi-path using a vertically polarized GNSS antenna with a rotationally symmetric pattern pointing to the horizon. In this work the conventional IPT is extended to dual-polarization, horizontal (H-pol) and vertical (V-pol), in attempt to increase the accuracy in the SM retrievals. In this case, the Brewster angle is estimated from the phase difference between the Hand V-Pol interference patterns. The use of dual-polarization measurements is not sensitive to surface roughness and it is more precise in the determination of the Brewster angle position. Results from a field experiment at the Yanco site, New South Wales, Australia, are shown to demonstrate the concepts proposed in this work.

Reflectometry using Global Navigation Satellite System's signals of opportunity (GNSS-R) was originally conceived in the early 90s for mesoscale altimetry, and since then, many studies have shown its applicability to other remote sensing applications. In 2002, the Remote Sensing Lab at the Universitat Politècnica de Catalunya started working in Global Navigation Satellite Reflectometry (GNSS-R) to perform a more accurate correction of the sea state when retrieving sea surface salinity from L-band microwave radiometer data (e.g. SMOS). During these 12 years, the lab has developed ground-based, airborne, balloon, and spaceborne GNSS-R payloads for a number of different applications. This paper provides an overview of the families of instruments, and the design choices made.

The Synthetic Aperture Interferometric Radiometer (SAIR) Performance Simulator (SAIRPS) is a very versatile software tool developed by Deimos Engenharia (Portugal) and the Universitat Politècnica de Catalunya-Barcelona Tech (Spain) for the European Space Agency to simulate and compute the figures of merit of the performance of arbitrary SAIRs, using the OpenSF framework. The description and developments of this simulator were previously reported in the open literature and previous IGARSS. This paper summarizes the developments in this third year of the project, including the end-to-end validation tests, and the radiative transfer module that has been added to improve the versatility of the tool.

Typhoon motoring using Global Navigation Satellite System (GNSS) signals is a new application of the GNSS-R technique, with increasing interest in the last years. Examples of that can be the CYGNSS (Cyclone Global Navigation Satellite System) spaceborne mission proposed by NASA, or the TIGRIS (Typhoon Investigation using GNSS-R Interferometric Signals) experiment, conducted in the framework of ESA-China cooperation. This paper focuses on the TIGRIS experiment, presenting the preliminary results obtained using the interferometric GNSS-R (iGNSS-R) technique.

The Microwave Interferometric Reflectometer (MIR) is a new airborne reflectometer being developed at Catalonia Polytechnic University (UPC) that uses Global Navigation Satellite Systems (GNSS) to retrieve mainly altitude over sea, but also soil, ice and sea parameters such as soil moisture, vegetation water content, sea surface roughness and wind speed. It uses two frequency bands and two different beams per band in order to improve the sensor capabilities. These beams point to the estimated specular reflection area and to the desired satellites considering the position of the platform.

Global Navigation Satellite System Reflectometry (GNSS-R) has been emerged as a new opportunity for satellite remote sensing. From the bistatic measurement of GNSS-R, various geophysical parameters can be retrieved. This work shows the possibility of GNSS-R to monitoring the tropical cyclone. For case study, the GEROS mission is considered, which plans to install GNSS-R instrument on International Space Station. From the simulated DDM, the scattering coefficient maps are restored, and the eye of cyclone is detected.

This paper describes the Microwave Interferometric Reflectometer (MIR) instrument back-end for GNSS reflectometry (GNSS-R) applications. MIR uses the interferometric (iGNSS-R) and conventional (cGNSS-R) techniques for altimetry and scatterometric observations. MIR is intended for low altitude aircrafts, and can track up to 4 pairs of satellite/reflection points simultaneously. The back-end computes real-time 2D cross-correlations in the delay/Doppler plane and performs incoherent averaging after proper delay and Doppler tracking. Initial results from ground measurements are shown.

Soil moisture (SM) is a key parameter in the climate studies at a global scale and a very important parameter in applications such as precision agriculture at a local scale. The Global Navigation Satellite Systems Interference Pattern Technique (IPT) has proven to be a useful technique for the determination of SM, based on observations at vertical polarization (V-Pol) due to the Brewster angle. The IPT can be applied at both V-Pol and horizontal polarization (H-Pol) at the same time, observing the Brewster angle only at V-Pol. This letter presents a measurement technique based on tracking the phase difference between V-Pol and H-Pol interference patterns to improve the accuracy of the Brewster angle determination and, consequently, that of the SM retrievals. This technique benefits from the different phase behavior of the reflection coefficients between H-Pol and V-Pol in the angular observation range. To be sensitive to the phase difference, the Rayleigh criterion for smooth surfaces must be accomplished. This technique is not sensitive to topography as it is intrinsically corrected. Experimental results are presented to validate the proposed algorithm.

This work focuses on the relationship between real and synthetic aperture radiometers giving a general and common mathematical framework for both of them. It will be demonstrated that a real aperture radiometer array can be understood as a synthetic aperture one, with a high level of redundancy. Therefore, all the recent results from synthetic aperture radiometry can be translated to real aperture radiometer arrays. This fact can be used to create beamforming arrays in a new way. To do this, the beamforming array equation will be written in terms of cross-correlations between all pair of antenna signals (visibility samples). By properly combining the visibility samples, a new type of digital beamforming radiometer can be implemented, which will benefit from the high calibration accuracy achieved in synthetic aperture radiometers (e.g., The Y-shaped MIRAS radiometer used in the Soil Moisture and Ocean Salinity mission of the European Space Agency) and the flexibility to electronically steer the beam.

Earth-reflected Global Navigation Satellite System (GNSS) have become an attractive tool to be employed in low-Earth-orbit spaceborne missions, for applications such as ocean mesoscale altimetry and scatterometry. For such techniques, several on-board processing strategies have been proposed, either based on the correlation with on-board generated signal or based on ‘blind’ interferometric processing, which involves the correlation between received direct and reflected signals. This paper will provide a comparison of these two proposed GNSS-R processing techniques, highlighting the possible achieved performance for a typical spaceborne scenario. The performance comparison will be carried out by analyzing the widely used Cramer-Rao Bound, which takes into account the full statistical properties of the reflected signals and provides accurate comparison.

This work presents a novel technique for the determination of soil moisture obtaining 2-D Soil Moisture (SM) information with a single instrument. Both the instrument and the retrieval algorithm used, which is based on inferring the reflection coefficient of the terrain by direct and forward scattering polarimetric measurements of Global Navigation Satellite Systems (GNSS) Signals, are briefly described. Some preliminary results of a field campaign performed on La Pobla de Mafumet (Tarragona, Spain) are presented. This instrument and retrieval algorithm can be used for different applications, such as, an input for the irrigation algorithm (Smart-Irrigation) or forest fire prevention among others.

Reflectometry using Global Navigation Satellite System's signals of opportunity (GNSS-R) was originally conceived for mesoscale altimetry, but it can be applied to sea state determination (i.e. wind speed), among many other applications. The feasibility to create scattering coefficient and wind speed maps over the ocean using the Delay-Doppler Maps (DDMs) has also been analyzed. In this work a case study is presented to show the evolution of some features of the DDM (shape and peak) as seen from a PAU-like GNSS-R instrument aboard the International Space Station (ISS), while overpassing the Sandy hurricane on October 27th, 2012 in front of the coast of Florida.

ESA's SMOS mission has been a cornerstone in passive Earth Observation, since it has provided for the first time ever with global and frequent observations of Soil Moisture and Ocean Salinity (where the mission acronym comes from). SMOS' single payload is MIRAS: the Microwave Imaging Radiometers by Aperture Synthesis in two dimensions. After SMOS' success, today, a number of instruments are planned or under study: the GeoStar instrument is the baseline payload for the Precipitation and All-weather Temperature and Humidity (PATH) mission from NASA (USA), the Geostationary Atmospheric Sounder (GAS) instrument is under study for post-MSG operational satellites observations (Europe), and the Geostationary Interferometric Microwave Sounder (GIMS) instrument from NSSC-CAS (China). The study of the instrument performance in terms of angular resolution and radiometric performance (radiometric sensitivity and accuracy), and the optimization of this new type of instruments is a complex task that requires dedicated ad-hoc tools. In this work the SAIRPS (Synthetic Aperture Interferometric Radiometer Performance Simulator) is presented. This complex simulator allows to analyze arbitrary receiver topologies, arbitrary array geometries, and includes noise injection calibration algorithms, and new external robust calibration algorithms, and image reconstruction algorithms that allow to evaluate the performance of almost any instrument. At present, the full simulator has been coded in Matlab, translated into C++, and integrated in OpenSF. This work summarizes the key aspects of the architecture of this simulator, completing the presentation made in IGARSS 2012, and presents a few examples of the simulation results using different instrument configurations.

Reflectometry using Global Navigation Satellite System's signals of opportunity (GNSS-R) was originally conceived for mesoscale altimetry [1], although its applicability to sea state determination, soil moisture, vegetation, snow monitoring... has already been demonstrated. In December 2012 the Phase A studies of ESA's PAssive Reflectometry and Interferometry System In-orbit Demonstration (PARIS IoD) mission ended. In conventional GNSS-R the GNSS signals scattered over the Earth's surface are cross-correlated with a locally generated replica of the transmitted signal shifted in frequency (Δfd) and in delay (Δτ). PARIS is called an interferometric GNSS-R (iGNSS-R) system because the direct and the scattered signals are cross-correlated in order to use the whole signal's bandwidth, and improve the altimetric precision, despite the large bandwidth signals are not publicly available. This work presents a methodology to evaluate the performance of iGNSS-R altimeters. It is then applied to a PARIS IoD-like case, in which the receivers' bandwidths have been optimized in terms of altimetric resolution.

A powerful real time Radio-frequency interference (RFI) mitigation back-end system is presented in this work. The interfering signals are estimated by using the wavelet transform to utilize its effective denoising capability. The estimated RFI signals are then subtracted from the total received signal, and ultimately the RFI-mitigated signal is obtained. Here, the hardware implementation and the system tests are demonstrated, showing sinusoid, chirp, and PRN interference mitigation under different Interference to Noise Ratios (INRs).

The use of Global Navigation Satellite Signals (GNSS) in reflectometric applications (GNSS-R) is highly extended in remote sensing applications, such as sensing sea state, soil moisture or ice layer characterization. There are two main techniques in this field: the conventional GNSS-R, that achieves high SNRs by cross-correlating the received signal with a replica of the transmitted one but, with a low resolution due to narrow bandwidth of the signals, and the interferometric GNSS-R, which achieves better resolutions but with lower SNRs since it directly correlates the direct and reflected signals. The Microwave Interferometric Reflectometer (MIR) is a new sensor that will use high-directivity, multiband and steerable arrays to achieve higher SNRs in the interferometric technique. Additionally, it will also apply the conventional technique. All these capabilities will be applied simultaneously to two beams at each band (L1 and L5 / E1 and E5). This work describes this concept instrument and the first prototypes will be presented at the conference.

PAU/PARIS End-to-end Performance Simulator (P2EPS) has been developed for studying and design tools for GNSS-R space mission. For the purpose of accuracy and various scenario, P2EPS has recently improved in many features. Especially, the wide range of the simulation inputs enables to simulate the upcomming GNSS-R space missions. This paper presents the recent improvement of the P2EPS.

In the last years, the GPS signals have been validated as opportunity signals in a wide range of reflectometry-based remote sensing applications for sea, land or ice scenarios. Recently, the first Galileo satellites have started transmitting the new signal E1, which shares the band with the GPS L1 signal. This work compares the performance of both signals in space and airborne scenarios for sea state and altimetry determination.

Tracking, in radar altimetry, is the positioning of the waveforms in the correlation window. This letter presents a tracking strategy in spaceborne altimetry using global navigation satellite system reflectometry. First, the tracking procedure is illustrated, and the tracking parameters are discussed one by one: the determination of the correlation window, the accuracy of specular delay guess, and the tracking-refresh period. Based on the results, the proposed European Space Agency Passive Reflectometry and Interferometry System In-Orbit Demonstrator tracking case study is examined.

This work presents the flight model of a PAU version to be flown in INTA's (Instituto Nacional de Técnicas Aeroespaciales, Spanish Aerospace Center) MicroSat-1 and the tests performed. PAU is a hybrid GNSS-Reflectometer / Microwave Radiometer developed to assess the impact of the sea state on the L-band brightness temperatures and on the GNSS-R observables (the Delay Doppler Maps or DDMs). The DDMs can be used in the future to perform the sea state correction in the L-band radiometric measurements, and therefore, improve the quality of the sea surface salinity retrievals. This work also describes a sensitivity test, a Doppler test, and a preliminary field experiment to evaluate the performance.

Reflectometry using Global Navigation Satellite System's (GNSS) opportunity signals was originally conceived for altimetry [1]. However, when the GNSS signals scatter over the Earth's surface (or propagates through the atmosphere), the amplitude and polarization characteristics change, which can be used for many other remote sensing applications such as sea state, water level, soil moisture, vegetation height, snow depth monitoring, atmospheric profiling... ([2], [3] among many others). In [4] and [5], recent experimental results from an ESA-sponsored airborne campaign carried out in June and November 2011 in the Baltic sea are presented using conventional and interferometric GNSS-R, respectively. In this work the properties of the measured interferometric GNSS-R waveforms are studied, and the wavelet transform is applied to compress and denoise the waveforms. This is of interest for future missions, such as ESA's proposal of PARIS IoD, to reduce the amount of data to be stored on board and downloaded to Earth.

ESA's SMOS mission has demonstrated that Synthetic Aperture Interferometric Radiometers can be a useful tool for Earth observation. Today, the NASA's GeoStar instrument (USA), ESA's GAS instrument (Europe), or CSSAR's GIMS instrument (China) are just three examples of planned geostationary millimeter-wave sounders using synthetic aperture interferometric radiometry for continuous atmospheric monitoring with a much improved spatial resolution. The study of the performance in terms of angular resolution and radiometric performance, and the optimization of this new type of instruments is a complex task that requires dedicated ad-hoc simulators. The SAIPRS (Synthetic Aperture Interferometric Radiometer Performance Simulator) is an ESA project aiming at the development of a generic simulator in terms of receiver architecture and array configuration, including moving antennas (and eventually changing polarization reference frames). This work summarizes the key aspects of the architecture of this simulator.

The ultimate accuracy and precision of conventional1 and interferometric2Global Positioning Satellite System Rerflectometry (GNSS-R) techniques for mesoscale ocean altimetry are still a matter of debate in the scientific community. The results obtained depend on the techniques used to identify the point of the specular delay in the waveform, and to perform the different delay corrections to derive the geometric delay. Also, the geometric model assumed for the scenario determines the accuracy of the altimeter range. This work presents the results of two ESA-sponsored airborne experiments using conventional GNSS-R showing subdecimeter altimetric precision with the Global Positioning System (GPS) L1 C/A code only. The Relative Mean Dynamic Topography (RMDT) obtained in both experiments is compared with results derived from traditional radar altimetry provided by Jason 2. The Root Mean Square (RMS) of the RMDT difference between both measurement systems is 48 cm for the first flight, and 198 cm for the second flight. Additionally, results from the second flight experiment show the capability of the proposed technique to retrieve sea slope measurements by superposing the ground track with EM96 geoid undulations.

The PARIS (Passive Reflectometry and Interferometry System) in orbit demonstrator is a novel altimeter concept recently proposed by the European Space Agency. PARIS has the primary objective of observing ocean mesoscale features using Global Navigation Satellite Systems (GNSS) reflected signals, with an expected sea surface height estimation accuracy of about 20 cm, and with a very high simultaneous spatial-temporal sampling of the ocean. To date, the altimetry performance has been preliminary predicted by means of simple analytical methods, which rely on a number of assumptions on the estimators, not predicting the optimum performance. This paper will present a prediction of the height precision based on the statistical analysis of the well-known Cramer-Rao estimation bound.

Earth-reflected Global Navigation Satellite System (GNSS) signals have become an attractive tool for remote sensing. Recently it has been proposed as an alternative to the conventional altimetry to estimate the surface height However GNSS-R altimetry offers lower bandwidths and signals power compared to radar altimeters. This implies a poorer altimetry precision, accuracy and resolution per pulse.Also the altimetry precision will be impacted by the impact of the thermal, and speckle noise mainly. This paper gives a critical review of the cross-correlation waveform model.

The compensation of the Doppler frequency error is important to accurately estimate the sea height in spaceborne GNSS-R altimetry. This work presents the impact of the residual Doppler error on the altimetric performance. The GNSS-R altimetric observables (waveforms) are simulated with various observation parameters, and the degradation is analyzed vs. the Doppler errors. It is shown that the Doppler error causes a bias, a decrease of the waveform value, and consequently the altimetric performance degradation in accuracy and precision.

This paper presents calibration and the radiometric performance of the Passive Advanced Unit Synthetic Aperture (PAU-SA) in order to verify the instrument's characterization.

In recent years GNSS-R has been proposed for ocean remote sensing, both for altimetry and scatterometry. For the later, two main approaches are available: fitting the measurements with a model, or using some observable from the measurements (either the waveform or the delay-Doppler Map) to be directly linked to ocean surface's roughness. For ground-based and airborne experiments, several direct observables have been proposed to describe ocean surface's roughness, and they have been used assuming that the observation geometry had little impact on them. However, it may not be true for a spaceborne scenario, since the dynamics are higher. In this work an extensive simulation study is performed, and the first results on how the observation geometry does impact different GNSS-R direct observables is presented.

Interpolation strategies for calibration of the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency are tested and compared. Calibration strategy (how and how often) is critical in achieving the required performance of any instrument, but it is even more important in very complex instruments such as the new family of synthetic aperture interferometric radiometers and, in particular, in the Microwave Imaging Radiometer by Aperture Synthesis instrument aboard the SMOS mission. On one hand, frequent calibration reduces the available observation time. On the other hand, the calibration requirements for soil moisture applications are more relaxed than those for ocean salinity, so the intercalibration time requirements are very different. Since SMOS drifts are stationary, half-orbit information is available to perform different interpolation strategies. In this letter, these approaches are tested to estimate the calibration parameters between consecutive calibrations. The average root-mean-square phase error is then used to find the optimum interpolation strategy and intercalibration time. On the other side, in real-time instruments, the “future” calibration data are not available at the time of taking the measurements, and predictors are required to estimate the evolution of the calibration parameters from past data only. For these systems, the extended Kalman filter can be used. The intercalibration time in a real-time instrument is evaluated, and the requirements and performances are compared to offline instruments.

Global navigation satellite system reflectometry has already shown its potential to perform retrievals of a number of geophysical parameters, including soil moisture, vegetation height, etc. This letter focuses on the study of snow-covered soils using the interference pattern technique (IPT) with the Soil Moisture Interference-pattern GNSS Observations at L-band (SMIGOL) reflectometer, a ground-based instrument. Snow effects are analyzed, and an algorithm has been developed for this type of surfaces. From November 2010 to May 2011, a long-term field experiment was carried out at the Pyrenees (Val d'Aran, Lleida, Spain) to test the IPT and the retrieval algorithms on snow-covered soils.

Global Navigation Satellite Systems (GNSS) opportunity signals reflected at or near the Earth's surface have already shown their potential to perform retrievals of a number of geophysical parameters. Radio occultations using GNSS signals are also used for atmospheric sensing. This letter presents a GNSS technique to retrieve vegetation water content (VWC). This technique measures the received powers of the GPS signals in open sky and under the vegetation layer. From these two powers, the attenuation due to the vegetation is computed, which is related to the VWC. This letter presents the results obtained after deploying the instrument in a walnut-tree stand for 11 months.

In recent decades, atmospheric scientists have been interested in measuring thermodynamic variables such as tropospheric water vapor and temperature with increasing temporal and spatial resolution due to their importance on the climate modeling. For this purpose, microwave radiometers have been used to measure columnar integrated water vapor. The radiative transfer equation (RTE) has been used to retrieve the contributions of individual atmospheric layers, assuming a stratified atmosphere. In recent years, significant advances have been made toward retrieval of these parameters in 2-D, 3-D and 4-D (3-D + time) distributions. This work presents a new radiometric concept to directly measure the contribution of each pixel (avoiding the use of the RTE inversion) by using pencil-beam antennas and interferometric techniques. This new approach has the potential to improve the quality of the retrieved thermodynamic variables to meet the research goals of atmospheric science.

Global Navigation Satellite System (GNSS) Reflectometry was originally proposed for mesoscale altimetry, but today its feasibility for sea state, soil moisture, vegetation and snow height has already been demonstrated. This paper describes a GNSS-Reflectometer develop to perform the sea state correction in L-band radiometric measurements, and therefore, improve the quality of the sea surface salinity retrievals. The instrument is currently being developed as a secondary payload to be launched aboard INTA (Instituto Nacional de Técnicas Aerospaciales, Spanish Aerospace Center) MicroSat-1. The basic principles of operation and the instrument development status are presented.

Reflectometry using Global Navigation Satellite System's (GNSS) opportunity signals was originally conceived for altimetry [1], but it has been demonstrated today that it can be applied to sea state determination, soil moisture, vegetation, snow monitoring... So far, GPS signals scattered over the Earth's surface have been cross-correlated with a local replica of the transmitted signal (typically the only GPS available: the C/A code) shifted in frequency (Δfd) and in delay (τ). However, to achieve the full potential (bandwidth) of these signals the direct and reflected signals can be directly cross-correlated, but in this case, high gain antennas are required to increase the signal-to-noise ratio. Therefore these antennas must be steerable so as to track the direct satellite and the specular reflection point. This is the concept of the European Space Agency PARIS In Orbit Demonstrator (IoD) mission [2], a new concept that was demonstrated experimentally for the first time in 2010 [3]. This work deals with the analysis of the preliminary instrument error budget of this mission to address the critical design parameters.

So far, GNSS-R studies on sea surface wind retrieval from Delay-Doppler Maps (DDM) have focused on the best fitting of the model to the measurements. This paper proposes a new approach to retrieve the sea surface wind using DDM deconvolution. The proposed method is based on the direct restoration of scattering coefficients from two measured DDMs. Using the restored scattering coefficient images, the sea surface slope is estimated, and eventually the wind speed is retrieved from the sea surface slope. This paper presents the performance of the proposed method with the simulation results, and the advantages of the method.

This paper presents the Passive Advanced Unit Synthetic Aperture instrument (PAU-SA), and some of the first experimental results: the use of pseudo-random noise signals for a complete baseline calibration and receivers' frequency response characterization, the use of a Kalman filter to better estimate the receivers' phase between internal calibrations, the imaging of an artificial point source at different angles and polarizations and, the first images of the GPS constellation satellites as they move in the instrument's field of view.

GNSS-R techniques are currently being studied to remotely sense a number of geophysical parameters over different types of surfaces [1-6]. The Interference Pattern Technique (IPT) is based on the measurement of the interference pattern of the GPS direct and reflected signals, after reflecting over the surface, as the GPS satellites move. This paper extends previous studies [7-11], in which water level was monitored [7] and land areas were observed retrieving soil moisture, topography and vegetation height for different kinds of crops (wheat, barley and maize) [8-10], to a snow- covered soils studies.

In the last decade GNSS-R techniques have started to be used for Earth remote sensing [1-7]. In previous studies, the Interference Pattern Technique (IPT) was used to observe land surfaces using a ground-based instrument: soil moisture over bare soils [8], surface's topography, soil moisture and vegetation height of wheat and barley fields [9], and a maize field (very dense and tall vegetation) [10], and snow height [11]. This work extends previous studies to the observation of the water level in a reservoir. Other GNSS-R techniques have addressed this problem previously, but it is shown that the extremely simple IPT outperforms them.

Global Navigation Satellite Systems' signals refiectometry, originally envisioned for ocean altimetry, has become a promising remote sensing technique. Among other applications, it has been proposed for ocean scatterometry for sea state determination. Most of the proposed scatterometry techniques have as a product an average sea state descriptor over the whole observed ocean region. However, a Delay-Doppler Map (DDM) measurement is actually collecting the scattered power in different points of the observed surface so it has been recently proposed to invert the DDM measurements in order to obtain the scattering coefficient (σ0) distribution over the observed surface. In this paper, this technique is applied to the numerical simulation of oil slicks detection.

The radiometric resolution of a motion-induced synthetic aperture radiometer (MISAR) is analytically obtained from the standard deviation of a baseline response, an observation scenario, and the imaging method of the MISAR. The intrinsic long integration time given by the whole dwell time on moving platforms improves the radiometric resolution compared with the snapshot resolution of other nominal synthetic aperture radiometers. In addition, it is illustrated that the MISAR imaging holds the tradeoff relationship between the radiometric and spatial resolutions.

Global navigation satellite system reflectometry of signals is a promising technique to remotely sense a number of Earth's geophysical parameters, and it has been proposed for ocean monitoring applications such as mesoscale altimetry or sea state monitoring. So far, the following two main approaches have been considered to retrieve a sea state descriptor from measured delay waveforms or delay-Doppler (DD) maps (DDMs): 1) fitting the measurements to a model tuned with the desired parameter or 2) directly linking a property of the measurements with the parameter to be retrieved (e.g., volume of the normalized DDM). However, these approaches provide a single sea state descriptor related to the overall glistening zone where sea state conditions may not be homogeneous. In this letter, the relationship between the physical space and the DD domains is exploited, and a method to retrieve the bistatic scattering coefficient distribution over the observation ocean surface from measured DDMs is proposed.

Global Navigation Satellite System's (GNSS) opportunity signals reflected over the surface of the Earth can be used for altimetry, sea state determination... So far, GPS signals scattered over the Earth's surface have been cross-correlated with a local replica of the transmitted signal (typically the GPS available C/A code) shifted in frequency (Δfd) and in delay (τ). However, it is not possible to achieve the full potential of these signals due to the unavailability of the large bandwidth codes. To overcome this problem, the direct and reflected signals can be cross-correlated. However, to improve the SNR high gain antennas are required and they must be steerable so as to point to the direct satellite and to the specular reflection point. Differences between the receivers' frequency responses impact the overall frequency response, and may distort the ideal observables. This work presents the analytical computation of the GNSS reflectometer observables in the above conditions and will compare them to the ideal ones, so as to be able to properly specify the receivers' frequency response.

This paper presents an end-to-end simulator to assess the performances of Global Navigation Satellite System Reflectometry (GNSS-R) space missions for altimetry or sea state determination. The presented simulator is capable of simulating the GNSS-R observation scenario including the states of the transmitting and receiving satellites, the full instrument modeling, and scattering physical modeling based on an actual geophysical database. It provides useful tools for research and development on GNSS-R remote sensing.

A 2-D Doppler-radiometer has been proposed to improve the poor angular resolution of microwave radiometers, using aperture synthesis on a moving platform. In this letter, we investigate drawbacks of the Doppler-radiometer, which have not been discussed previously in detail. The imaging method is revised to be suitable for imaging of distributed sources, which is the more common situation than a point source, and then the specklelike sidelobes in the point source response are discussed. In distributed source imaging, the specklelike sidelobes in the point source response of the Doppler-radiometer severely degrade the imaging performance, so it is necessary to reduce them. The cause of specklelike sidelobes is discussed, and a sparse array is proposed to improve the imaging performance of the Doppler-radiometer. The improvement is demonstrated by simulation of the point source response, showing reduced speckle.

In this paper, we present the design and calibration of the fully polarimetric radiometer at 94 GHz. For stable and high sensible Stokes parameters measurements, we applied a wideband analog correlator and a total power type receiver with a periodic calibration. To perform the fully polarimetric calibration, a calibration standard was designed and tested. Using the calibration standard, the calibration gain-offset was estimated and evaluated. The measured sensitivities with the integration time of 10 ms are approximately 1.26 K and 1.27 K in the horizontal and vertical channels, respectively. Other performances of the developed system and the calibration are also described and discussed.

In this paper, high spatial resolution imaging of a motion induced synthetic aperture radiometer with sparse rectangular array is presented. The imaging process is described including an observation scenario and image formation. The equivalent array factor and instantaneous spatial frequency coverage are presented to demonstrate the performance. Additionally, the differences between the proposed system and previous studies are discussed.

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Dual-channel Radiometers for Earth and Atmosphere Monitoring (DREAM) is the Korean first spaceborne radiometer which is the main payload of Science and Technology SATellite-2 (STSAT-2). The satellite will be launched by Korea Space Launch Vehicle-1 (KSLV-1) at NARO Space Center in Korea in 2007. DREAM is a two-frequency, total power microwave radiometer with linear polarization. It measures the brightness temperature of the Earth at 23.8 and 37 GHz. In this paper, the characteristics and the preliminary design of DREAM are described.

This article evaluates the performance of interferometric synthetic aperture radiometer using sub-Y-type array proposed by our research group, SSL at GIST, Korea. The proposed array type has an improved resolution than the conventional Y-type known as optimal array configuration in the design of 2-D interferometric radiometer. To evaluate it, the interferometric synthetic aperture radiometer with 40 antenna array is developed at 37 GHz and two target noise sources were used for performance test. Through the experiments, the performance evaluation shows 23% improvement of angular resolution than the conventional Y-type

The monitoring techniques of red tide at present have been studied based on satellite remote sensing with optical and infrared band. In this article, a new approach to red tide monitoring at microwave and millimeter-wave frequency is proposed. To evaluate this idea, the dual frequency radiometer system with L- and W-band was implemented. The experiments were performed on a coastal area of southern sea in Korea to do in-situ test on August and September in 2003. The experiment results show that the red tide could be distinguished from clean seawater by the brightness temperature and detected using microwave radiometry