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Even though reflectometry using Global Navigation Satellite System's signals (GNSS-R) was first envisioned for mesoscale ocean altimetry, nowadays a number of different applications have been developed (ocean scatterometry, ice monitoring, soil moisture retrieval, etc.). Recently, imaging of the ocean surface from a GNSS-R spaceborne receiver has been proposed by treating the measured delay-Doppler Maps (DDM) as a blurred image of the surface's scattering coefficient in the delay-Doppler domain. Thus, by deconvolving the DDM with the GNSS code Woodward ambiguity function (WAF), and appropriate domain transform, an image of the surface's scattering coefficient distribution can be obtained. In this work this technique is applied to oil slick detection. A realistic scenario is simulated, and the performance of the GNSS-R imaging technique is evaluated on the retrieved image. Error below 10% in the retrieved scattering coefficient distribution is achieved (except for regions affected by deconvolution artifacts), and the image resolution of the order of 2 km is comparable to that of a synthetic aperture radar (SAR) system with equivalent specifications.

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.

The Soil Moisture and Ocean Salinity (SMOS) mission is an Earth Explorer Opportunity mission from the European Space Agency (ESA). Its goal is to produce global maps of soil moisture and ocean salinity using the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS). The purpose of the Passive Advanced Unit Synthetic Aperture (PAU-SA) instrument is to study and test some potential improvements that could eventually be implemented in future missions using interferometric radiometers such as the Geoestacionary Atmosferic Sounder (GAS), the Precipitation and All-weather Temperature and Humidity (PATH) and the Geostationary Interferometric Microwave Sounder (GIMS). Both MIRAS and PAU-SA are Y-shaped arrays with uniformly distributed antennas, but the receiver topology and the processing unit are quite different. The purpose of this work is to identify the elements in the MIRAS’s design susceptible of improvement and apply them in the PAU-SA instrument demonstrator, to test them in view of these future interferometric radiometer missions.

This study provides a general framework to analyze the effects on correlation radiometers of a generic quantization scheme and sampling process. It reviews, unifies and expands several previous works that focused on these effects separately. In addition, it provides a general theoretical background that allows analyzing any digitization scheme including any number of quantization levels, irregular quantization steps, gain compression, clipping, jitter and skew effects of the sampling period.

In the past years, the scientific community has placed a special interest in remotely sensing soil moisture and vegetation parameters. Radiometry and radar techniques have been widely used for years. Global Navigation Satellite Systems opportunity signals Reflected (GNSS-R) over the earth's surface are younger, but they have already shown their potential to perform these observations. This paper presents a GNSS-R technique, based on Global Positioning System (GPS) measurements, that allows the retrieval of several geophysical parameters from land surfaces. This technique measures the power of the interference signal between the direct GPS signal and the reflected one after scattering over the land, so it is called Interference Pattern Technique (IPT). This paper presents the results obtained after applying the IPT for topography, soil moisture, and vegetation height retrievals over vegetation-covered soils.

This paper presents the description and performance tests of an L-band microwave radiometer with Digital Beamforming (DBF), developed for the Passive Advanced Unit (PAU) for ocean monitoring project. PAU is an instrument that combines, in a single receiver and without time multiplexing, a microwave radiometer at L-band (PAU-RAD) and a GPS-reflectometer (PAU-GNSS-R). This paper focuses on the PAU‑RAD beamformer’s first results, analyzing the hardware and software required for the developed prototype. Finally, it discusses the first results measured in the Universitat Politècnica de Catalunya (UPC) anechoic chamber.

The feasibility of the Global Navigation Satellite Signal Reflectometry (GNSS-R) techniques has been proven for remote determination of sea state. When using GNSS-R techniques, coherent integration time is limited by the correlation time of the surface under observation which, in the case of the ocean, depends on sea state. In this letter, a new technique to retrieve the sea correlation time at L-band using GNSS-R coherent data is presented along with experimental results.

A new and efficient algorithm to compute delay-Doppler maps is presented. It improves by more than an order of magnitude the required computation time and memory resources. This approach is based on the derivation of explicit expressions of the space coordinates as a function of the delay offset and Doppler shift. Using this technique, the limitation posed by the number of sampling points of the observed surface is drastically attenuated, and a wide range of scenarios from low- to medium-height airborne-to-spaceborne scenarios can now be simulated with standard desktop computers.

This paper presents an efficient procedure based on 2-D convolutions to obtain delay-Doppler maps (DDMs) of Global Navigation Satellite Signals reflected (GNSS-R) over the sea surface and collected by a spaceborne receiver. Two DDM-derived observables (area and volume) are proposed to link the sea-state-induced brightness temperature to the measured normalized DDM. Finally, the requirements to use Global Positioning System reflectometry to accurately correct for the sea state impact on the L-band brightness temperature (quantization levels, decimation, truncation, and noise impact) are analyzed in view of its implementation in the Passive Advanced Unit instrument of the Spanish Earth Observation Satellite (SeoSAT/INGENIO) project.

This work describes a novel dual-band Global Navigation Satellite Systems Reflectometer (GNSS-R) that uses the P(Y) and C/A signals scattered over the sea surface to perform highly precise altimetric measurements. The results derived from two different ground-based field experiments over a dam and over the sea under different surface's roughness conditions are presented. The analysis of the altimetric performance shows that the results obtained using the P(Y) code improve by a factor between 1.4 and 2.4 as compared to the results obtained using the C/A code, respectively, for high and mid-low satellite's elevation angles.

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 crosscorrelations 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-shapedMIRAS radiometer used in the Soil Moisture and Ocean Salinity mission of the European Space Agency) and the flexibility to electronically steer the beam.

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 European Space Agency Passive Reflectometry and Interferometry System In-orbit Demonstrator (IoD) aims to perform mesoscale altimetric observations by measuring the Global Navigation Satellite System (GNSS) opportunity signals reflected over the sea surface. Altimetry based on GNSS reflectometry (GNSS-R) is significantly affected by satellite motion, since it requires relatively long integration times to reduce noise. We present the impact of the satellite motion on the GNSS-R observables and the need to retrack the waveforms. By using a detailed GNSSR space mission simulator, the change of delay difference between the direct and the reflected signals during the incoherent averaging of the waveform has been investigated. Their effects on the waveform shape and the altimetric performance are presented comparing the aligned and non-aligned waveforms. Results show that the performance of spaceborne GNSS-R altimeter is seriously degraded without a proper alignment of the waveform samples.

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 groundbased 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.

[1] Reflectometry using Global Navigation Satellite Systems signals (GNSSR) has been the focus of many studies during the past few years for a number of applications over different scenarios as land, ocean or snow and ice surfaces. In the past decade, its potential has increased yearly, with improved receivers and signal processors, from generic GNSS receivers whose signals were recorded in magnetic tapes to instruments that measure full Delay Doppler Maps (the power distribution of the reflected GNSS signal over the 2-D space of delay offsets and Doppler shifts) in real time. At present, these techniques are considered to be promising tools to retrieve geophysical parameters such as soil moisture, vegetation height, topography, altimetry, sea state and ice and snow thickness, among others. This paper focuses on the land geophysical retrievals (topography, vegetation height and soil moisture) performed from a ground-based instrument using the Interference Pattern Technique (IPT). This technique consists of the measurement of the power fluctuations of the interference signal resulting from the simultaneous reception of the direct and the reflected GNSS signals. The latest experiment performed using this technique over a maize field is shown in this paper. After a review of the previous results, this paper presents the latest experiment performed using this technique over a maize field. This new study provides a deeper analysis on the soil moisture retrieval by observing three irrigation-drying cycles and comparing them to different depths soil moisture probes. Furthermore, the height of the maize, almost 300 cm, has allowed testing the capabilities of the technique over dense and packed vegetation layers, with high vegetation water content.

[1] Reflectometry using GNSS signals of opportunity (GNSS-R) has stood as a powerful technique for ocean remote sensing. Particularly, the use of these techniques has been proposed to retrieve sea state information (i.e. sea surface roughness) among other applications. Precise knowledge of the sea state is a key issue to process L-band radiometric measurements for sea surface salinity retrieval. It has been recently shown that GNSS-R data can be directly linked to the brightness temperature variations caused by the sea state effect, without the use of emission/scattering models or sea spectra models. In this study, this approach is applied to CoSMOS 2007 flights data. Firstly, the radiometric and GNSS-R data sets are presented. Secondly, measured brightness temperature is corrected using the collocated GNSS-R data. In particular, the area under the normalized waveforms is used to directly compute the required brightness temperature correction. Thirdly, the salinity retrievals are presented (achieving an error reduction from 2.8 psu for the raw measurements down to 0.51 psu). Finally, the obtained results are compared with the WISE correction approach, based on the wind speed correction, and the conclusions of this work are presented.

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.

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.

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.

Sea surface salinity is a key oceanographic parameter that can be measured by means of L-band microwave radiometry. The measured brightness temperatures over the ocean are influenced by the sea state, which can entirely mask the salinity signature. Sea-state corrections parameterized in terms of wind speed and/or significant wave height have proven not to be fully satisfactory. In 2003, it was proposed to use reflectometry using navigation opportunity signals [Global Navigation Satellite System Reflectometer (GNSS-R)] for sea-state determination and correction of the measured L-band brightness temperature changes associated to the sea state. The novelty of the approach relies in the measurement of the whole Delay-Doppler Map that captures the scattering of the GNSS signals in the whole glistening zone. In this framework, the “Advanced L-BAnd emissiviTy and Reflectivity Observations of the Sea Surface” (ALBATROSS) field experiments were undertaken in 2008 and 2009, collecting an extensive data set of collocated radiometric and reflectometric measurements over the Atlantic Ocean, as well as oceanographic and meteorological data. In this paper, the experimental results and conclusions of the ALBATROSS 2009 field experiment are compiled and presented, showing the great potential of this technique to perform the necessary corrections in future salinity missions. Empirical relationships are derived among measured brightness temperature variations due to the sea-state effect and direct GNSS-R observables, and the sea surface correlation time at L1 band, a key parameter for GNSS-R data processing since it determines the maximum coherent integration time, was experimentally determined.

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.

The Global Navigation Satellite Signals Reflections (GNSS-R) techniques have been widely used for remote sensing purposes retrieving geophysical parameters over different types of surfaces. Over the ocean, altimetry [1, 2] or sea state [3, 4] can be retrieved. Over land, soil moisture [5, 6] can be inferred and over ice, altimetry, and ice age [7] are also retrieved. This paper presents the results of using GNSS-R techniques to retrieve altimetry from the measurements of an airborne GNSS-Reflectometer.

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.

This paper presents the current state of the Passive Advanced Unit Synthetic Aperture's instrument (PAU-SA), its installation in the transportation truck, and the preliminary tests that have been performed to verify the instrument's status.

Within the ESA's SMOS CAL/VAL activities, the GPS and Radiometric Joint Observations (GRAJO) field experiment was conducted. Apart from contributing to the SMOS CAL/VAL, the main purpose of the GRAJO experiment was to study the synergy of L-band radiometry and GNSS Reflectometry for soil moisture retrieval. Long-term experiments under controlled conditions. During one of these intensive short term experiments, the griPAU instrument (a Delay-Doppler Map GNSS-R receiver) was set up. The first results derived from the griPAU measurements are presented.

Sea Surface Salinity (SSS) is a very important oceanographie parameter that can be measured using L-band microwave radiometry. The measured brightness temperature measured over the ocean is influenced by the sea state that can even mask the salinity signature. Reflectometry using navigation signals (GNSS-R) has been proven to achieve sea state determination and has been proposed to be used to correct the measured brightness temperature for the sea state effect. In this framework, the "Advanced L-BAnd emissiviTy and Reflectivity Observations of the Sea Surface 2009" (ALBATROSS 2009) field experiment was undertaken collecting an extensive dataset of collocated radiometnc and reflectometnc measurements. In this paper the experimental results and mam conclusions of the ALBATROSS 2009 field experiment are presented.

The use of Global Navigation Satellite Signals Reflections (GNSS-R) techniques to retrieve geophysical parameters from surfaces has been increased in the recent years. These techniques have resulted in suitable tools to obtain information about the sea state of oceans, which is very useful to improve the ocean salinity retrieval [1–3], and also, information about the soil moisture [4–6] of lands. The present work focuses on the use of the Interference Pattern Technique (IPT) [7–10], a particular type of GNSS-R technique, to study vegetation-covered soils. The IPT consists mainly of the measurement of the interference pattern between the GPS direct and reflected signals (the interference power), after they impinge over the ensemble soil surface and vegetation layer. The measured interference signal provides information on the soil moisture of the surface and also, on the vegetation height.

The sea surface salinity (SSS) retrieval using microwave radiometry is seriously affected by the sea surface roughness. Global Navigation Satellite Signals Reflected (GNSS-R) have been proposed to perform this roughness correction. The selected observable is the volume of the normalized delay-Doppler map (maximum amplitude equal to one) above a threshold. This observable is related to the extension of the glistening zone, which is related to the sea state. Its validity to account for the surface roughness m terms of significant wave height (SWH) was proved during the ALBATROSS 2008 measurement campaign. In the following ALBATROSS 2009 campaign collocated measurements of instantaneous radiometnc brightness temperatures and GNSS-R volumes are obtained by two antennas pointing exactly to the same spot with the same beamwidth and beam properties. This work described the preliminary results of these field experiments.

So far a number of models have been developed to estimate the emission of the sea surface at L-band as a function of different key physical variables, such as the Sea Surface Temperature (SST), the Sea Surface Salinity (SSS) and the roughness as well as the presence of sea foam, but none has demonstrated to clearly perform better than the others. An important contribution in that direction will be given by the Soil Moisture and Ocean Salinity (SMOS) mission in the next future, when global and frequent measurements of the ocean will be available and, jointly with in-situ measurements collected by buoys or vessels, will permit further studies. To rehearse and optimally prepare the future analyses, two field experiments (the Advanced L-BAnd Transmission and Reflection Observations of the Sea Surface — ALBATROSS 2008 and 2009 -) have been carried out in one of the SMOS Calibration and Validation sites: The North Atlantic Subtropical Gyre. Brightness temperature measurements, using L-band real aperture radiometers, jointly with the reflected GPS signal, and in-situ measurements of SSS, SST, wind speed, and wave spectrum were collected during these experiments. The measurements have been analyzed and the first results of this analysis are presented. After an introductory section, the campaign set-up and the measurement procedure is described in section II, while the data processing is explained in section III. Finally, section IV is devoted to the presentation of the preliminary results of the study.

This paper presents the current state and preliminary results of the Passive Advanced Unit Synthetic Aperture's instrument (PAU-SA) [1] validation tests. The performed test has been focused on the implementation of the PAU-SA's interface in order to test extended source simulations. Moreover, the currently status of the hardware instrument is presented.

The Passive Advanced Unit (PAU) for ocean monitoring is a novel instrument that combines, in a single receiver and without time multiplexing, a microwave radiometer at L-band (PAU-RAD) and a GPS-reflectometer (PAU-GNSS/R). These two sensors together with an infra-red radiometer (PAU-IR) will simultaneously provide the sea surface temperature and the sea state information needed to accurately retrieve sea surface salinity. This paper presents the developed PAU-RAD hardware and software that will allow to obtain a digital radiometer with digital beamformer. After the introduction to the PAU concept presented in section 1, in secton 2 the concept of Digital Beamforming is detailed. Section 3 is devoted to the developement of PAU-RAD and, finally, the main conclusions of this work are resumed in section 4.

The Passive Advanced Unit (PAU) for ocean monitoring is a new type of instrument that combines in a single receiver and without time multiplexing, a polarimetric pseudo-correlation microwave radiometer at L-band (PAU-RAD) and a GPS reflectometer (PAU-GNSS/R). These instruments in conjunction with an infra-red radiometer (PAU-IR) will respectively provide the sea surface temperature and the sea state information needed to accurately retrieve the sea surface salinity from the radiometric measurements. PAU will consist of an array of 4x4 receivers performing digital beamforming and polarization synthesis both for PAU-RAD and PAU-GNSS/R. A concept demonstrator of the PAU instrument with only one receiver has been implemented (PAU-One Receiver or PAU-OR). PAU-OR has been used to test and tune the calibration algorithms that will be applied to PAU. This work describes in detail PAU-OR’s radiometer calibration algorithms and their performance.

The calibration of large aperture synthesis interferometric radiometers such as the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) aboard ESApsilas SMOS mission is a crucial issue. Due to the large number of receiving channels, calibration techniques based on the centralized noise injection from a single noise source would require a large and stable distribution network, which is unfeasible from the point of view of mass, volume and phase equalization. Distributed noise injection techniques have been proposed, but are unable to correct for all types of errors. This work analyzes the possibility of using pseudo-random noise (PRN) instead of a centralized noise source. PRN sequences are signals with very long repetition period and relatively flat spectrum over a bandwidth determined by the length of the sequence and the symbol rate. Since their spectrum looks like that of the noise, calibration of a microwave correlation radiometers can benefit from their use.

It is generally accepted that the best way to retrieve sea surface salinity (SSS) is by means of L-band radiometry (1400-1427 MHz). However, in addition to the polarization and the incidence angle, the SSS and the sea surface temperature (SST), the sea surface brightness temperature depends on the sea state. This work describes a hybrid L-band radiometer & GPS L1 reflectometer proposed to infer sea state information at similar surface roughness scales and therefore improve the sea state correction in surface salinity estimates.

This paper presents the first results of a hybrid synthetic aperture interferometric radiometer-GPS reflectometer called Passive Advanced Unit-Synthetic Aperture (PAU-SA). These tests are focused in the PAU-SA's performance with preliminary results at baseline level in order to characterize the radiometer part. The tests performed are: characterization of the radiometer noise and its stability through "Allan's variance", radiometric sensitivity, calibration of the offset errors and baseline response to a point source at different angles and polarizations.

In ESA's SMOS mission it is expected to improve the sea surface salinity retrieval using multi-angular information to correct for sea state effects. A multi-beam, digitally steered radiometer with polarization synthesis has been proposed for the first time as a part of the PAU instrument (Passive Advanced Unit for the ocean monitoring project). This paper provides theoretical and experimental results of extending the calibration algorithms of a digital radiometer obtained in to any number of receivers in order to achieve the digital beamforming.

GNSS-R techniques have been used to retrieve altimetric and sea state information in ocean scenarios. This paper provides theoretical and experimental results of using Global Navigation Satellite Signals reflected (GNSS-R) over bare soil and vegetation-covered soil to retrieve soil moisture using the measurement of the power of the interferent field (direct + scattered).

This paper presents the description and first results on the performance of a light-weight airborne L-band radiometer. This radiometer will be used in the SMOS CAL/VAL activities in the REMEDHUS site (Salamanca, Spain). First, a brief description of the overall system is presented. The first results obtained during a field experiment over the Ebro river mouth are then presented. These include flights over the sea shore (fresh and sea water) and land (dry and irrigated rice fields). This field experiment has also served to test the aircraft and the data processing algorithms that will be used in future campaigns with PAU-ORA, a reduced airborne demonstrator version of the PAU instrument.

The reflections of Global Navigation Satellite systems such as GPS can be used to retrieve geophysical parameters. A promising application is to use them for the sea surface roughness-induced corrections in the brightness temperature to retrieve the Sea Surface Salinity. A tandem campaign to obtain simultaneous radiometer and reflectometer data has been conducted on the North-West coast of the Gran Canaria Island (Canary Islands, Spain). The first results after processing the GNSS-R data are presented.

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS).

This paper describes some potential improvements that could be eventually implemented for future MIRAS (Microwave Imaging Radiometer by Aperture Synthesis) payloads of the follow-on missions of the ESA's SMOS (Soil Moisture and Ocean Salinity) mission. A ground-based instrument concept demonstrator has been designed and it is being implemented to validate these improvements. Both MIRAS and the (Synthetic Aperture Passive Advanced Unit, SA-PAU) are Y shaped arrays, but the receiver topology and the processing unit are significantly different. This paper identifies the elements in the MIRAS's design that could be improved and presents a new instrument (Synthetic Aperture PAU) that could be used to test some potential improvements for future SMOSops (SMOS operational system).

This work describes the PAU-IR instrument, an infrared radiometer used to estimate the sea surface temperature for sea surface salinity retrievals. The results of numerical simulations to predict the impact of different effects (rain, clouds, visibility) is presented with the theory to accurately retrieve the sea surface temperature. Finally, the results of a field experiment carried out 40 km South of Barcelona are presented.