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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.

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.

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 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.

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.

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 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.

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).

Sea surface salinity can be remotely measured by means of L-band microwave radiometry. However, the brightness temperature also depends on the sea surface temperature and on the sea state, which is probably today one of the driving factors in the salinity retrieval error budgets of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission and the NASA-Comision Nacional de Actividades Espaciales Aquarius/SAC-D mission. This paper describes the Passive Advanced Unit (PAU) for ocean monitoring. PAU combines in a single instrument three different sensors: an L-band radiometer with digital beamforming (DBF) (PAU-RAD) to measure the brightness temperature of the sea at different incidence angles simultaneously, a global positioning system (GPS) reflectometer [PAU-reflectometer of Global Navigation Satellite Signals (GNSS-R)] also with DBF to measure the sea state from the delay-Doppler maps, and two infrared radiometers to provide sea surface temperature estimates. The key characteristic of this instrument is that both PAU-RAD and the PAU-GNSS/R share completely the RF/IF front-end, and analog-to-digital converters. Since in order to track the GPS-reflected signal, it is not possible to chop the antenna signal as in a Dicke radiometer, a new radiometer topology has been devised which makes uses of two receiving chains and a correlator, which has the additional advantage that both PAU-RAD and PAU-GNSS/R can be operated continuously and simultaneously to perform the sea-state corrections of the brightness temperature. This paper presents the main characteristics of the different PAU subsystems, and analyzes in detail the PAU-radiometer concept.

It has come to our attention that in the original version of a paper published in Sensors recently, the names of four co-authors were misspelled with several hyphens missing. [...]

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 years Global Navigation Satellite System’s signals Reflectometry (GNSS-R) has stood as a potential powerful remote sensing technique to derive scientifically relevant geophysical parameters such as ocean altimetry, sea state or soil moisture. This has brought out the need of designing and implementing appropriate receivers in order to track and process this kind of signals in real-time to avoid the storage of huge volumes of raw data. This paper presents the architecture and performance of the Global Positioning System (GPS) Reflectometer Instrument for PAU (griPAU), a real-time high resolution Delay-Doppler Map reflectometer, operating at the GPS L1 frequency with the C/A codes. The griPAU instrument computes 24 x 32 complex points DDMs with configurable resolution (DfDmin = 20 Hz, Dsmin = 0.05 chips) and selectable coherent (minimum = 1 ms, maximum = 100 ms for correlation loss Dq < 90%)and incoherent integration times (minimum of one coherent integration period and maximum not limited but typically