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Camps, Adriano ... et al.-- Special volume: Planet Ocean. Scientia Marina 80(Suppl.1) 2016.-- 14 pages, 20 figures, [EN] This article summarizes some of the activities in which Jordi Font, research professor and head of the Department of Physical and Technological Oceanography, Institut de Ciències del Mar (CSIC, Spanish National Research Council) in Barcelona, has been involved as co-Principal Investigator for Ocean Salinity of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Mission from the perspective of the Remote Sensing Lab at the Universitat Politècnica de Catalunya. We have probably left out some of his many contributions to salinity remote sensing, but we hope that this review will give an idea of the importance of his work. We focus on the following issues: 1) the new accurate measurements of the sea water dielectric constant, 2) the WISE and EuroSTARRS field experiments that helped to define the geophysical model function relating brightness temperature to sea state, 3) the FROG 2003 field experiment that helped to understand the emission of sea foam, 4) GNSS-R techniques for improving sea surface salinity retrieval, 5) instrument characterization campaigns, and 6) the operational implementation of the Processing Centre of Levels 3 and 4 at the SMOS Barcelona Expert Centre, [ES] Este artículo resume algunas de las actividades en las que Jordi Font, profesor de investigación y jefe del Departamento de Física y Tecnología Oceanográfica, del Institut de Ciències del Mar (CSIC) en Barcelona, ha estado desarrollando como co-Investigador Principal de la parte de la misión SMOS de la ESA, una misión Earth Explorer, desde la perspectiva del Remote Sensing Lab, de la Universitat Politècnica de Catalunya. Seguramente, estamos olvidando algunas de sus muchas contribuciones a la teledetección de la salinidad, pero esperamos que esta revisión dé una idea de la importancia de su trabajo. Este artículo se focaliza en los siguientes puntos: 1) las medidas de alta calidad de la constante dieléctrica del agua marina, 2) las campañas de medidas WISE y EuroSTARRS que ayudaron a la definición del modelo geofísico relacionando la temperatura de brillo con el estado del mar, 3) la campaña de medidas FROG 2003 que ayudó a entender la emisión de la espuma marina 4) presentación de las técnicas de GNSS-R para la mejora de la recuperación de la salinidad superficial 5) campañas para la caracterización del instrumento y 6) la implantación del centro de procesado operacional de niveles 3 y 4 en el SMOS Barcelona Expert Centre, This work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05 and ESP2007-65667-C04, AYA2008-05906-C02-01/ESP, AYA2010-22062-C05 and ESP2015-70014-C2-1-R, and EURYI 2004 award

Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The results indicated that the camera performed consistently and that the data processing was consistent, as well. During the agricultural experiments, promising results were obtained for biomass estimation when the spectral data was used and when an appropriate radiometric correction was applied to the data. Our results showed that the new FPI technology has a great potential in precision agriculture and indicated many possible future research topics. peerReviewed

This article summarizes some of the activities in which Jordi Font, research professor and head of the Department of Physical and Technological Oceanography, Institut de Ciències del Mar (CSIC, Spanish National Research Council) in Barcelona, has been involved as co-Principal Investigator for Ocean Salinity of the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Mission from the perspective of the Remote Sensing Lab at the Universitat Politècnica de Catalunya. We have probably left out some of his many contributions to salinity remote sensing, but we hope that this review will give an idea of the importance of his work. We focus on the following issues: 1) the new accurate measurements of the sea water dielectric constant, 2) the WISE and EuroSTARRS field experiments that helped to define the geophysical model function relating brightness temperature to sea state, 3) the FROG 2003 field experiment that helped to understand the emission of sea foam, 4) GNSS-R techniques for improving sea surface salinity retrieval, 5) instrument characterization campaigns, and 6) the operational implementation of the Processing Centre of Levels 3 and 4 at the SMOS Barcelona Expert Centre., Este artículo resume algunas de las actividades en las que Jordi Font, profesor de investigación y jefe del Departamento de Física y Tecnología Oceanográfica, del Institut de Ciències del Mar (CSIC) en Barcelona, ha estado desarrollando como co-Investigador Principal de la parte de la misión SMOS de la ESA, una misión Earth Explorer, desde la perspectiva del Remote Sensing Lab, de la Universitat Politècnica de Catalunya. Seguramente, estamos olvidando algunas de sus muchas contribuciones a la teledetección de la salinidad, pero esperamos que esta revisión dé una idea de la importancia de su trabajo. Este artículo se focaliza en los siguientes puntos: 1) las medidas de alta calidad de la constante dieléctrica del agua marina, 2) las campañas de medidas WISE y EuroSTARRS que ayudaron a la definición del modelo geofísico relacionando la temperatura de brillo con el estado del mar, 3) la campaña de medidas FROG 2003 que ayudó a entender la emisión de la espuma marina 4) presentación de las técnicas de GNSS-R para la mejora de la recuperación de la salinidad superficial 5) campañas para la caracterización del instrumento y 6) la implantación del centro de procesado operacional de niveles 3 y 4 en el SMOS Barcelona Expert Centre.

Se trata de mejorar las imágenes del satélite SMOS del que la UPC tiene acceso a los datos. Sobre los oceanos es necesario mejorar la calidad de las imágenes para todas las aplicaciones relacionadas con la salinidad. This Degree Thesis has been performed at the Remote Sensing Laboratory (RSLab), at the Department of Signal Theory and Communications of the Universitat Politècnica de Catalunya. It consists on a set of strategies devoted to enhance the calibration system of the SMOS satellite. Along this manuscript, the basics of 2D interferometry are introduced as well as a brief review of the SMOS mission evolution. In order to understand SMOS calibration system the fundamental equations are also outlined. From there on, new calibration strategies are introduced, offering re-processing methods whose main aim is enhancing SMOS final products, such as salinity maps. The results were presented at the 26th meeting of the calibration group from the SMOS Expert Support Lab (ESL) . Este trabajo de fin de grado (TFG) ha sido realizado en el Remote Sensing Laboratory (RSLab) del Departamento de Teoría y Señal de Comunicaciones (TSC) de la Universidad Politécnica de Cataluña. El trabajo consiste principalmente en un conjunto de estrategias cuyo objetivo final es mejorar el sistema de calibración del satélite SMOS. A lo largo de esta memoria, los principios básicos de la interferometría 2D serán introducidos así como una breve explicación de la evolución de la misión SMOS. Con el objetivo de entender el sistema de calibración de SMOS las ecuaciones fundamentales serán destacadas. A partir de entonces, nuevas estrategia de calibración serán analizadas, basándose principalmente en métodos de reprocesado cuyo objetivo principal es aumentar la calidad de los productos finales de SMOS, como por ejemplo, mapas de salinidad globales. Los resultados de este proyecto han sido presentados en el 26º congreso del grupo de calibración del SMOS Expert Support Lab (ESL) . Aquest treball de fi de grau (TFG) ha estat realitzat al Remote Sensing Laboratory (RSLab) del Departament de Teoria i Senyal de Comunicacions (TSC) de la Universitat Politècnica de Catalunya. El treball consisteix principalment en un conjunt d?estratègies que tenen com a objectiu final millorar el sistema de calibració del satèl·lit SMOS. Al llarg d?aquesta memòria, els principis bàsics de la interferometria 2D seran introduïts així com una breu explicació de l?evolució de la missió SMOS. Amb l?objectiu de comprendre el sistema de calibració de SMOS, les equacions fonamentals seran esmentades. Dit això, noves estratègies de calibració seran analitzades, basant-se principalment en mètodes de reprocessat amb l?objecti final d?augmentar la qualitat dels productes finals de SMOS, com per exemple, mapes de salinitat globals. Els resultats d?aquest projecte han estat presentats en el 26é congrés del grup de calibració del Expert Support Lab (ESL) .

Analysis of the effects of the correction GKJ on SMOS data in the retrieval process of soil moisture Análisis de los efectos de la corrección GKJ en datos SMOS en el proceso de recuperación de humedad en tierra. Anàlisis dels efectes de la correcció GKJ en dades SMOS en el procés de recuperació d'humitat en la terra.

This paper provides a wrap-up of some of the activities undertaken by SMOS L1 team to fine tune the instrument calibration and modeling that eventually has resulted into a SMOS full-polarimetric measurement and image reconstruction enhanced performance

This work will assess and analyse the observed reconstruction error in SMOS brightness temperature images, to improve further the accuracy of the data, which would allow new scientific breakthroughs. The floor error (or noise floor) is defined as the time-averaged spatial ripple that remains after an image reconstruction process, assuming perfect knowledge of the instrument and no calibration errors. The noise error is therefore completely independent of the radiometric noise or the presence of modelling errors, being then solely related with the reconstruction process, su [ANGLÈS] The European Space Agency (ESA) Soil Moisture and Ocean Salinity mission (SMOS) provides continuous global maps of soil moisture and ocean surface salinity. Its payload MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) is an L-band (1400 MHz - 1427 MHz) interferometric radiometer which achieves unprecedented spatial resolution at this frequency. It was successfully launched on the 2nd November 2009 under the European Space Agency Earth Explorer program, and is now acquiring high precision data. Although the analysis presented here has been performed in the framework of SMOS, the conclusions are also valid for other types of missions using Synthetic Aperture Radiometers for observing planetary surfaces from space. This work analyzes the observed reconstruction error in SMOS brightness temperature images, to improve further the accuracy of the products, which would allow new scientific advances. The reconstruction error is defined as the residual spatial ripple that remains after an image reconstruction procedure, assuming perfect knowledge of the instrument and no calibration errors. The spatial ripple is therefore completely independent of the radiometric noise or the presence of modeling errors, being then solely related to the reconstruction process, summarized by the reconstruction matrix G. It will be shown that a condition which makes this error to appear is to have small antenna patterns differences between the receivers. In the case of SMOS, antenna voltage patterns differ by up to 5% of the nominal peak value. These differences, among other smaller contributions, introduce the undesired spatial ripple in the processed images, which cannot be improved using Gibbs-reduction techniques. After several years in orbit providing very useful data to the scientific community, it has become clear that to make new scientific breakthroughs possible, a complete re-assessment of the reconstruction process must be carried on, emphasizing on the non-idealities of the real instrument. The understanding of the theoretical roots of the reconstruction error in the non-ideal case is the first step on improving the performance of the instrument. Therefore, the reconstruction error is defined precisely using linear algebra, and its origins are investigated. To validate the theoretical results, several simulations have been performed using a custom-built SMOS simulator. In addition, this work proposes a new family of error correction techniques, which do not use any model of the scene. These techniques are based in a pre-distortion of the reconstruction matrix G, to mitigate the spatial ripple. Their performance is first assessed through simulations and, finally, with real SMOS data. [CASTELLÀ] La misión de la ESA (Agencia Espacial Europea) SMOS (Soil Moisture Ocean Salinity) genera continua y globalmente mapas de humedad del suelo y salinidad oceánica superficial. Su payload, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) es un radiómetro interferométrico de banda L (1.400 MHz - 1427 MHz), que alcanza resoluciones sin precedentes en esta frecuencia. Se lanzó con éxito el 2 de noviembre de 2009 bajo el programa de la ESA Earth Explorers, y actualmente adquiere datos de alta precisión. Aunque la presente tesis se ha hecho bajo el marco de SMOS, sus conclusiones son también válidas para otras misiones utilizando radiómetros interferométricos para observar superficies planetarias desde el espacio. Este trabajo analiza el error de reconstrucción observado en las imágenes de temperatura de brillo de SMOS, para mejorar aún más la precisión de los productos, lo que permitiría nuevos avances científicos. El error de reconstrucción se define como la ondulación espacial residual que permanece después de un procedimiento de reconstrucción de la imagen, asumiendo el conocimiento perfecto del instrumento y que no hay errores de calibración. Por tanto, la ondulación espacial es completamente independiente del ruido radiométrico o la presencia de errores de modelado, siendo entonces exclusivamente relacionado con el proceso de reconstrucción, que se resume con la matriz de reconstrucción G. Una condición que induce a este error a aparecer es tener pequeñas diferencias entre los patrones de antena de los receptores. En el caso de SMOS, los patrones de antena difieren hasta un 5% del valor máximo nominal. Estas diferencias, entre otras contribuciones más pequeñas, introducen ondulaciones espaciales no deseadas en las imágenes procesadas, las cuales no se pueden mejorar utilizando técnicas basadas en reducción del efecto Gibbs. Después de varios años en órbita que han proporcionado datos muy útiles a la comunidad científica, ha quedado claro que para hacer posible nuevos avances científicos, una nueva evaluación completa del proceso de reconstrucción debe llevarse a cabo, con énfasis en las no idealidades del instrumento. La comprensión de las raíces teóricas del error de reconstrucción en el caso ideal es el primer paso para mejorar el rendimiento del instrumento. Por lo tanto, el error de reconstrucción es definido aquí con precisión utilizando álgebra lineal, y sus orígenes son investigados. Para validar los resultados teóricos, varias simulaciones se han realizado utilizando un simulador de SMOS hecho a medida. Además, este trabajo propone una nueva familia de técnicas de corrección de error, que no utilizan ningún modelo de la escena. Estas técnicas se basan en una predistorsión de la matriz de reconstrucción G, para mitigar las oscilaciones. Su capacidad de mejorar el error de reconstrucción es evaluada primero a través de simulaciones y, finalmente, con datos reales de SMOS. [CATALÀ] La missió de la ESA (Agència Espacial Europea) SMOS (Soil Moisture Ocean Salinity) genera continua i globalment mapes d'humitat del sòl i salinitat oceànica superficial. El seu payload, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) és un radiòmetre interferomètric de banda L (1400 MHz - 1427 MHz), que aconsegueix resolucions sense precedents a aquesta freqüència. Es va llençar amb èxit el 2 de novembre de 2009 sota el programa de l’ESA Earth Explorers, i actualment adquireix dades d’alta precisió. Tot i que la present tesi s’ha fet sota el marc d’SMOS, les seves conclusions són també vàlides per altres missions utilitzant radiòmetres interferomètrics per observar superfícies planetàries des de l’espai. Aquest treball analitza l'error de reconstrucció observat en les imatges de temperatura de brillantor d’SMOS, per millorar encara més la precisió dels productes, el que permetria nous avenços científics. L'error de reconstrucció es defineix com l'ondulació espacial residual que roman després d'un procediment de reconstrucció de la imatge, assumint el coneixement perfecte de l'instrument i que no hi ha errors de calibratge. Per tant, l'ondulació espacial és completament independent del soroll radiomètric o la presència d'errors de modelatge, sent llavors exclusivament relacionat amb el procés de reconstrucció, que es resumeix amb la matriu de reconstrucció G. Una condició que indueix a aquest error a aparèixer és tenir petites diferències entre els patrons d'antena dels receptors. En el cas de SMOS, els patrons de antena difereixen fins a un 5% del valor màxim nominal. Aquestes diferències, entre altres contribucions més petites, introdueixen ondulacions espacials no desitjades en les imatges processades, les quals no es poden millorar utilitzant tècniques basades en reducció de l’efecte Gibbs. Després de diversos anys en òrbita que han proporcionat dades molt útils a la comunitat científica, ha quedat clar que per fer possible nous avenços científics, una nova avaluació completa del procés de reconstrucció ha de portar-se a terme, amb èmfasi en les no idealitats de l'instrument. La comprensió de les arrels teòriques de l'error de reconstrucció en el cas no ideal és el primer pas per millorar el rendiment de l'instrument. Per tant, l'error de reconstrucció és definit aquí amb precisió utilitzant àlgebra lineal, i els seus orígens són investigats. Per validar els resultats teòrics, diverses simulacions s'han realitzat utilitzant un simulador de SMOS fet a mesura. A més, aquest treball proposa una nova família de tècniques de correcció d'error, que no utilitzen cap model de l'escena. Aquestes tècniques es basen en un predistorsió de la reconstrucció de la matriu G, per tal de mitigar l'ondulació espacial. La seva capacitat de millorar l’error de reconstrucció és avaluada primer a través de simulacions i, finalment, amb dades reals d’SMOS.

This paper develops an analysis of the SAR impulse response function from the interferometric point of view, with the intention of studying its phase behavior in the presence of high squint angle values. It will be pointed out that in this case, a phase ramp is present in the range direction, which, in combination with a certain degree of misregistration between the two images induces an offset in the generated interferometric phase. This behavior, if not compensated, imposes strong limits on the performance of the interferometric techniques in a squinted case, especially for airborne SAR systems. The article proposes two new techniques, which are appropriate to correct the phase bias coming from this source. The first one is based on a modification of the azimuth compression filter, which cancels the phase ramp of the range impulse response function for one specific squint value. In case the SAR processing is performed with variable squint over range, the authors propose a second method oriented to estimating the expected misregistration and thus, the phase bias by means of an iterative approach. Simulated data as well as real corner reflector responses are used to show that the correct topography can be recovered precisely even in the presence of phase bias coming from the squinted geometry.

10 pages, 14 figures, 1 tabl3, The local oscillators (LOs) of the Soil Moisture and Ocean Salinity mission payload are used to shift the operating frequency of the 72 receivers to an optimal intermediate frequency needed for the signal processing. The LO temperature variations produce phase errors in the visibility, which result in a blurring of the reconstructed brightness temperature (Tb) image. At the end of the commissioning phase, it was decided to calibrate the LO every 10 min while waiting for a more in-depth analysis. During short periods of time, the LO calibration has been performed every 2 min to assess the impact of a higher calibration rate on the quality of the data. In this paper, by means of a decimation experiment, the relative errors of 6- and 10-min calibration interval data sets are estimated using the 2 min as a reference. A noticeable systematic across- and along-track pattern of amplitude $pm$0.3 K is observed for Tb differences between 10 and 2 min, whereas this is reduced between 6 and 2 min. A simulation experiment confirms that the nature of such systematic pattern is due to the visibility phase errors induced by the LO calibration rate. Such pattern is propagated into the sea surface salinity (SSS) retrievals. Overall, the SSS error increase (relative to the 2 min SSS data) is about 0.39 and 0.14 psu for the 10- and 6-min data sets, respectively. This paper shows that a LO calibration rate of at least 6 min would noticeably improve the SSS retrievals, The SMOS Level 2 Prototype Processor development was funded by the European Space Agency under different contracts

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14–0.18. In the corrected data, the homogeneity was 0.10–0.12 with a correction based on broadband irradiance measured in UAV, 0.07–0.09 with a correction based on spectral irradiance measurement on ground, and 0.05–0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

Bightness-temperature retrieval techniques for synthetic aperture radiometers are reviewed. Three different approaches to combine measured visibility and antenna temperatures, along with instrument characterization data, into a general equation to invert are presented. Discretization and windowing techniques are briefly discussed, and formulas for reciprocal grids using rectangular and hexagonal samplings are given. Two known techniques are used to invert the equation, namely, inverse Fourier transform and G-matrix pseudoinverse. The proposed preprocessing approaches combined with these two inversion methods are implemented with real data measured by an airborne Y-shaped interferometric radiometer over land and water, and are compared. The images indicate that best results are obtained when inverting an incremental visibility obtained after substracting a term that includes the individual antenna temperatures, the physical temperatures of the receivers, and a flat-target response directly measured from cold-sky looks.

The on-ground characterization of the synthetic aperture radiometer onboard the Soil Moisture and Ocean Salinity mission is described. Characterization includes basic functionality, internal calibration, thermal cycling, response to point and flat sources, self-radio-frequency interference, and others. The description of the different tests performed as well as the detailed results are provided. The results show that the instrument is very stable and has all gains and offsets consistent with the ones obtained at subsystem level. On the other hand, the phase of the visibility has a larger variation with temperature than expected, a small signal leakage from the local oscillators is present, and a small interference from the X-band transmitter during short periods of time has been detected. The implementation of internal-calibration procedures, along with the accurate thermal characterization performed, have been used to produce highly accurate brightness-temperature values well within specifications.

Speckle noise represents one of the major problems when synthetic aperture radar (SAR) data are considered. Despite the fact that speckle is caused by the scattering process itself, it must be considered as a noise source due to the complexity of the scattering process. The presence of speckle makes data interpretation difficult, but it also affects the quantitative retrieval of physical parameters. In the case of one-dimensional SAR systems, speckle is completely determined by a multiplicative noise component. Nevertheless, for multidimensional SAR systems, speckle results from the combination of multiplicative and additive noise components. This model has been first developed for single-look data. The objective of this paper is to extend the single-look data model to define a multilook multidimensional speckle noise model. The asymptotic analysis of this extension, for a large number of averaged samples, is also considered to assess the model properties. Details and validation of the multilook multidimensional speckle noise model are provided both theoretically and by means of experimental SAR data acquired by the experimental synthetic aperture radar system, operated by the German Aerospace Center.

This paper reviews the relative calibration of an interferometric radiometer taking into account the experimental results of the first batch of receivers developed in the frame of the European Space Agency's Soil Moisture and Ocean Salinity mission. Measurements show state-of-the-art baseline performance as long as the system is capable of correcting the effect of orbital temperature swing. A method to validate internal calibration during in-orbit deep-sky views and to correct linearity errors is also presented.

The spatial resolution of current space-borne Earth observation radiometers is limited by the physical antenna aperture. This is especially critical at L-band, which exhibits high sensitivity to soil moisture and sea surface salinity. Interferometric radiometers (InR's) are currently being studied by several space agencies as a feasible alternative to overcome this problem. However, their calibration is a crucial issue since most techniques inherited from radio astronomy cannot be directly applied. Due to the large number of receiving channels, calibration techniques based on centralized noise injection from a single noise source will require a large and stable distribution network, which is technically very complex and unacceptable from the point-of-view of mass and volume. Procedures based on distributed noise injection from a set of noise sources through smaller distribution networks have been recently proposed by the authors as an alternative to alleviate these technological problems. In this paper, the analysis of these networks, the impact of the noise generated by the network losses on the calibration, and the impact of front-end reradiated noise are analyzed. Finally, the optimum circuit topologies and tolerances to which these networks have to be characterized in order to achieve the required calibration are derived. These configurations are formed by cascading basic 1:2 and 1:3 isolated power splitters. Isolators at receiver inputs have to be included in order to minimize offsets originating from the correlation of reradiation of receiver noise. It has been found that, in order to satisfy the calibration requirements of InR's, the S-parameters of the ensemble noise-injection network plus isolators have to be known to within 0.025-0.050 dB in amplitude and 0.5° in phase, and their physical temperature known to within 0.5°C.

In Earth observation programs there is a need of passive low frequency (L-band) measurements to monitor soil moisture and ocean salinity with high spatial resolution 10-20 km, a radiometric resolution of 1 K and a revisit time of 1-3 days. Compared to total power radiometers aperture synthesis interferometric radiometers are technologically attractive because of their reduced mass and hardware requirements. In this field it should be mentioned the one-dimensional (1D) linear interferometer ESTAR developed by NASA and MIRAS a two-dimensional (2D) Y-shaped interferometer currently under study by European Space Agency (ESA). Interferometer radiometers measure the correlation between pairs of nondirective antennas. Each complex correlation is a sample of the “visibility” function which, in the ideal case, is the spatial Fourier transform of the brightness temperature distribution. Since most receiver phase and amplitude errors can be hardware calibrated, Fourier based iterative inversion methods will be useful when antenna errors are small, their radiation voltage patterns are not too different, and mutual coupling is small. In order to minimize on-board hardware requirements-antennas, receivers and correlators-the choice of the interferometer array shape is of great importance since it determines the (u,v) sampling strategy and the minimum number of visibility samples required for a determined aliasing level. In this sense, Y-shaped and triangular-shaped arrays with equally spaced antennas are optimal. The main contribution of this paper is a technique that allows the authors to process the visibility samples over the hexagonal sampling grids given by Y-shaped and triangular-shaped arrays with standard rectangular FFT routines. Since no interpolation processes are involved, the risk of induced artifacts in the recovered brightness temperature over the wide held of view required in Earth observation missions is minimized and signal to noise ratio (SNR) is preserved.

The fundamental concept of interferometric aperture synthesis microwave radiometry for Earth observation is reviewed. The measurement principles and a discussion on the signal processing techniques for image reconstruction are briefly summarized. Examples of real measurements from the sensor onboard the ESA SMOS mission are used to illustrate the image reconstruction techniques.