This work introduces the ongoing initiatives by the "RFI in Remote Sensing Working Group" within the IEEE Standards Association. The Working Group is taking the lead in standardizing the evaluation of radio frequency interference (RFI) impact on spaceborne microwave remote sensing. This standardization effort aims to enhance the monitoring of RFI and improve the effectiveness of sharing information related to it. It is developing a standard titled "P4006 Standard for Remote Sensing Frequency Band Radio Frequency Interference (RFI) Impact Assessment". This paper presents these efforts and highlights the recent activities undertaken by this working group.

In this paper, we describe the attempt of the Frequency Allocation in Remote Sensing Technical Committee (FARS-TC) from the IEEE Geoscience and Remote Sensing Society (GRSS) to standardize the impact assessment of radio frequency interference (RFI) especially in the field of spaceborne remote sensing. Multiple radio services have been sharing a common radio band with remote sensing satellites, resulting in inevitable interferences between each other. In other cases, some services accidentally emit their signal to nearby frequency band. Detecting interference and locating its source is a necessary task to guarantee data integrity. Given that remote sensing satellites carry unique payloads, the effect that RFI have depends on each sensor. For this reason, the RFI impact assessments have been usually developed with one mission or application in mind.Standardizing the impact assessment of RFI will benefit to make a public identification system so that we can monitor RFI effectively. In this paper, we introduce the working group in the IEEE Standards Association named "P4006 Standard for Remote Sensing Frequency Band Radio Frequency Interference (RFI) Impact Assessment" which is handled by the IEEE GRSS FARS-TC and its recent activities.

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA), together with NASA's Soil Moisture Active Passive (SMAP) mission, is providing a wealth of information to the user community for a wide range of applications. Although both missions are still operational, they have significantly exceeded their design life time. For this reason, ESA is looking at future mission concepts, which would adequately address the requirements of the passive L-band community beyond SMOS and SMAP. This article proposes one mission concept, TriHex, which has been found capable of achieving high spatial resolution, radiometric resolution, and accuracy, approaching the user needs. This is possible by the combination of aperture synthesis, formation flying, the use of general circular orbits, and alias-free imaging.

The IEEE Geoscience and Remote Sensing Society Frequency Allocation in Remote Sensing Technical Committee triggered the development of one IEEE Standard to quantify the quality of the remote sensing frequency bands allocated to Earth Observation with respect to RFI. This abstract describes the current status of the Standard development.

The European Space Agency (ESA) has recently published the Soil Moisture and Ocean Salinity Mission (SMOS) third mission reprocessing data, which include the changes in calibration and image reconstruction that have been made to the Level 1 Operational Processor (L1OP) version v724 during the past few years. The new L1 processor incorporates several improvements to the calibration and image reconstruction algorithms. The present article proposes a new methodology used by the SMOS team to evaluate the quality and stability of the L1 data. This is done by comparison with an ocean forward model over a well-known, sea-surface salinity stable, region. The L1 reprocessed radiometry accuracy and stability are studied in detail. The results presented here confirm the improvement on data quality expected for the new baseline algorithm. Furthermore, the remaining biases and open points are described and analyzed, establishing the basis for their improvement in following reprocessing campaigns.

The Faraday Rotation (FR) is a non-negligible effect at the L-band, which is the operation frequency of the Soil Moisture and Ocean Salinity (SMOS) mission. This effect introduces a rotation in the electromagnetic field polarization when propagating through the ionosphere that must be compensated. Recently, a methodology was developed in order to retrieve the Vertical Total Electron Content (VTEC) from SMOS radiometric data with the aim to better correct the Faraday rotation effect [1]. In that work, systematic patterns in the retrieved Faraday Rotation Angle (FRA) were detected. In this paper, these systematic patterns are characterized and corrected to improve the quality of the retrieved VTEC maps. These maps can be then re-used in the SMOS level 2 processor for the correction of the FRA in the mission. The impact of using the SMOS-derived VTEC maps instead of the VTEC data from GPS measurements on the ocean brightness temperature measurement has also been analyzed. Results of this analysis show that the usage of those maps allows a significant enhancement in the quality of the brightness temperatures, which will lead to an improvement on salinity retrievals.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 11 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps being fully operational. This II-year long lifetime of SMOS, so far, has enabled the calibration and Level-1 processor team to improve the calibration procedures and the image reconstruction resulting in a new version of the Level-1 data processor, v724. To present the main performance features of this new version and the improvement in the calibration procedures constitute the main objective and content of this presentation.

Radio Frequency Interference (RFI) is a growing threat to all Earth Observation (EO) passive microwave missions. Many RFI detection algorithms are used on-board and in the ground segment data processing, but there is no single algorithm that can detect all RFI instances. The best strategy is always to combine several detection methods. This paper presents the results of the new Ground RFI Detection System (GRDS). The GRDS uses a combination of a wide variety of RFI detection algorithms to clean the Earth Observation measurements from RFI. The system is built to be able to scan for RFI for any EO mission. The initial results show the important reduction on RFI in the EO data as measured by the European Center for Mid-Range Weather Forecast (ECMWF) first guess departure statistics.

Radio Frequency Interference (RFI) is a major concern for both real and synthetic aperture radiometers. After the lessons learnt from SMOS, ESA is preparing the next generation of L-band interferometric radiometers with RFI mitigation integrated into the cross-correlators. This work presents a preliminary design and results of a pre-correlation RFI mitigation algorithm tailored for interferometric radiometers. The results show that the correlation error introduced by the RFI is reduced on average to the half, with peaks of 20 dB of mitigation.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission was launched 2 Nov 2009 and, to date, is still in good health, providing valuable L-band observations of the Earth surface [1]. A number of products are obtained from these, including thin sea ice [2], frost/thaw soils [3], high winds [4], ocean surface wind [5] and Sun brightness temperature [6], besides the main mission measurements of soil moisture and sea surface salinity [7] [8]. This paper deals with the description and early results of some technology activities conducted by ESA applying the lessons learnt by SMOS and in preparation of an advanced L-band radiometer mission.

The important task of deciding and revising frequency allocations at international level falls under the responsibility of the World Radiocommunication Conference (WRC) which is organized by a specialized agency of the United Nations, the Radiocommunications Sector of the International Telecommunications Union (ITU-R). A WRC is held every approximately four years for the purpose of updating the international Radio Regulations (RR). The most recent of these conferences, WRC-19, held at the end of 2019, also defined the Agenda Items for the next WRC that is scheduled to occur in 2023. Here, we review and discuss the WRC-23 Agenda Items that are likely to have the most impact on future remote sensing operations.

Radio Frequency Interference (RFI) is a serious constraint affecting the Earth Observation (EO) passive microwave missions whose effect has been increasing. There is no single algorithm that can detect all RFI instances. The best strategy always is to combine several detection methods. This paper presents a new system concept: Ground RFI Detection System (GRDS). The GRDS uses a wide variety of RFI detection algorithm to clean the Earth Observation measurements from RFI. The system architecture is modular and it is built to be able to scan for RFI for any EO mission. The initial assessments reported show the potential for this GRDS system.

Radio-frequency interference (RFI) has had a detrimental effect on L-band passive observatories such as SMOS, Aquarius and SMAP. A better knowledge of the characteristics of RFI signals might help mitigate this issue by leading to additional and better focused RFI detection algorithms and it might help identify RFI emitters on the ground. In this study we present approaches to retrieve some of the features of the RFI signals using SMAP data and we present some statistical considerations about the temporal and spectral characteristics of RFI sources.

Temporal stability of the radiometer MIRAS, on board the SMOS satellite, is analyzed using long series of data spanning for about 6 years. Brightness temperature retrieved from one orbit per day over the Pacific Ocean is compared against a forward model and the difference between both is analyzed. Plots of the average in central latitudes as a function of time show small seasonal ripples (~±0.5 K) that depend on the calibration strategy chosen. An extremely low drift of only several mK/year is found and in some cases disappears. Hovmoller plots for the same data, consisting of brightness temperature biases as a function of latitude and time, confirm the small ripples and show some latitude dependent structures, probably coming from geophysical signatures.

The ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit over nine years, with its L-Band Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) functioning well. Between October 2011 and March 2012, a sudden increase in the distribution of RF interference (RFI) was observed over most urban areas in Japan, and this RFI scenario has remained unchanged during the last years. The interference has also polluted the observations of the SMAP (Soil Moisture Active/Passive) and Aquarius missions operated by NASA. This case of harmful interference was reported by ESA to the Japanese Regulatory Authorities in accordance to the procedure contained in the ITU Radio-Regulations. Investigations have shown that the main RFI source is originated by the aggregate radiations from the intermediate frequency (IF) circuits of broadcasting-satellite receiving installations. The main RFI causes appear to be due to poor quality cable, poor connections and/or issues with installation practices resulting in insufficient RF screening. This paper presents the SMOS experience in addressing this unique RFI problem encountered, provides an overview of the investigations conducted and the on-going actions led by the Japanese authorities in order to mitigate the impact of the interference.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 9 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data products are generated using version v620 of the Level-1 operational processor, a version which entered into operation in Spring 2015. During last year a comprehensive data set was processed using a new processor version v720 and the assessment of the results is expected to be completed by mid 2019. In parallel to this evaluation of v720, the following version v730 of the Level-1 processor of SMOS has been already produced. This latter version is intended for investigating the capability to reduce Radio Frequency Interferences (RFI) by applying image processing techniques. This paper describes the major features and status of the two mentioned versions of the SMOS Level-1 processor, and importantly, aims at updating the remote sensing community on those aspects of the SMOS mission.

Microwave remote sensing relies on the utilisation of the electromagnetic spectrum, which is becoming a precious commodity due to increasing demand by commercial telecommunication and other radio services. The access to this resource is regulated by the International Telecommunication Union, which periodically holds a World Radiocommunication Conference (WRC) where representatives from different countries meet to define international rules for its use.The next WRC will take place in November 2019, and the Frequency Allocations in Remote Sensing (FARS) Technical Committee of the IEEE Geoscience and Remote Sensing Society (GRSS) has prepared a report discussing the Agenda Items of the conference that are most relevant to remote sensing. This contribution will explain the issues at stake for remote sensing at WRC-19, illustrate the document conclusions and provide suggestions on what remote sensing scientists and engineers can do to become more involved in tackling these issues.

A new technique to mitigate Radio Frequency Interference (RFI) contamination for SMOS images was recently proposed. The technique consists in extrapolating the measured brightness temperature (BT) frequencies in the u/v coverage map outside the star coverage of SMOS. This technique has been implemented, and the quality improvements have been assessed with means of a triple collocation technique using SMOS and SMAP data.

The quality of the Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) maps has been noticeably improved in the last two years, in particular those produced at the Barcelona Expert Center (BEC). However, the BEC SSS maps are still affected by a latitudinal and seasonal bias. In this work, we comprehensively characterize the residual latitudinal and seasonal biases, which are used to correct de retrieved SSS, leading to a new generation of higher-quality SSS maps. The shape and regularity of this bias suggests that the effect, which produces this error, is not a poor characterization of the galaxy, some residual Total Electron Content (TEC) effect, or a poor characterization of the systematic Sea Surface Temperature (SST) effects on the SSS retrieval. It appears to be related to a geometrical effect associated to the relative position between the SMOS antenna, the Sun and the Earth.

The SMOS (Soil Moisture and Ocean Salinity) satellite was launched on 2 November 2009, and it is the ESA second Earth Explorer Opportunity mission. After almost 10 years of successful Operations, the status of the SMOS mission is excellent. However, SMOS observations are significantly affected by RF interference (RFI) in several world areas.Since the first SMOS mission observations, its radiometer in the passive band 1400-1427 MHz detected RFI sources. Any emission in this band is prohibited by ITU Radio-Regulations (RR No.5340) [1]. To successfully accomplish the decrease in the global number of interfering sources, two parties are required: SMOS RFI team - to detect, monitor and report the cases of harmful interference - and national regulatory authorities - to investigate and take remedial actions to solve the RFI case (i.e. remove unauthorized devices, fix malfunctioning equipment or optimize operational settings). Some examples of devices causing interference are presented in this paper, showing the impact on the SMOS science data according to the topology of the interfering device.

Radio Frequency Interferences (RFI) are still an important source of contamination in SMOS data. The application of nodal sampling (NS) to brightness temperature images helps to mitigate the degradation that RFIs produce in geophysical retrievals. Nodal sampling has been extensive and successfully tested over open ocean and in the proximity to coastal regions. In this work, we assess the performances of NS over strongly RFI-contaminated ocean regions, particularly over semi-enclosed seas. These regions are especially challenging because of the strong contamination caused by the nearby RFI sources over land and the residual land-sea contamination.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission [1] has been in orbit for over 8 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data for this whole period has been and is being processed with the operational version of the current Level-l processor (version v620). Also a representative part of the same data set has been processed with a working version of a new processor (v720) which is now in preparation so that homogenous records of brightness temperatures have been made available. These rich and long data records have allowed learning important lessons from the in-flight experience, and shall eventually lead into the consolidation of the new Level-l processor version (v720) with its corresponding auxiliary calibration and configuration files. Once the improvements are confirmed the new processor version shall be recommended for the operational chain.

A new technique to mitigate Radio Frequency Interference (RFI) contamination for SMOS images is proposed. The technique consists in extrapolating the measured brightness temperature (BT) frequencies in the u/v coverage map outside the star coverage of SMOS. The results show an important reduction of the RFI contamination.

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission operates in the 1400-1427MHz frequency band, which is allocated to the EESS(passive) service in the ITU Radio-Regulations. The measurements of SMOS radiometer are perturbed by radio frequency interferences (RFIs) that jeopardize part of its scientific retrieval in certain areas of the World. This paper summarizes the strategies initiated by the European Space Agency to mitigate the impact of RFIs, and in particular the collaboration established with national telecommunication Authorities for the investigation of interference cases and switching-off the unauthorised RFI sources. The RFI detection, monitoring and reporting process is described in more detail, focused on the tasks carried out by the SMOS Operations team at ESAC, the ESA centre located near Madrid. The RFI tools developed and the planned evolution are also presented.

The Soil Moisture Active/Passive (SMAP) satellite mission measures Earth's radiation in the protected portion of the spectrum at 1.413 GHz (L-band) to retrieve geophysical quantities of the surface, such as soil moisture and the frozen/thawed state of the soil. The presence of radio-frequency interference (RFI) in this band is significant and impacts the quality of SMAP measurements. Knowing the location of the sources of RFI is important, because it can help to identify the source itself and also be used to develop strategies to mitigate its impact of the RFI on the data. This paper presents an algorithm that takes advantage of the viewing geometry of SMAP to locate sources of RFI. The results are validated using known locations of RFI sources and by comparison with the measurements of Soil Moisture and Ocean Salinity (SMOS) and Aquarius, two other satellite missions with L-band microwave radiometers operating in the protected band. Comparison with RFI of known location suggests that the algorithm is accurate to 1-2 km. The median distance between the locations reported by SMOS and this algorithm is 2.27 km. A study of the relationship between the localization error and the number of observations of RFI sources shows that the median localization error is about 2 km with 12 observations and about 1 km with 30 observations.

It has recently been found that the visibility denormalization process introduces a spatial error distribution due to small sporadic offset jumps in the PMS detectors. The radiometric impact of this error at system level is very low. However, due to the good performance of the SMOS instrument, a study has recently been conducted to evaluate the amplitude of such visibility errors and develop a mitigation technique. The main results of this study are summarized in this presentation.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for over 7 years, with its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) functioning well. This 7 year period has provided a wealth of information which has enabled us to understand and consolidate the performance of the payload in great detail. More importantly, we know now the things that work well, those that need improvement, and how the instrument could be enhanced if we were to build it again. This paper presents the lessons learnt from SMOS after 7 years in orbit.

The SMOS mission is a joint program led by ESA with participation of CNES in France and CDTI in Spain. SMOS satellite carries a single payload on board, MIRAS, a Microwave Imaging Radiometer with Aperture Synthesis. The satellite has been in-orbit for over 7 years, providing for the first time and for this entire time, the longest record of space-sensed soil moisture and ocean salinity measurement [1], as well as new applications such as measurements of thin ice thickness [2] and surface ocean winds in storms [3].

ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for over 6 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps working well. The data for almost this whole period has been reprocessed with the new fully polarimetric version (v620) of the Level-1 processor which also includes refined calibration schema for the antenna losses. This reprocessing has allowed the assessment of an improved performance benchmark, a better understanding of the observations, and the preparation of a new version (v700) of the Level-1 processor with further potential.

The Soil Moisture and Ocean Salinity (SMOS) mission by the European Space Agency (ESA) was launched in 2009 [1]. Since then, it has produced a continuous stream of valuable geophysical data over land, ice and ocean [2] However, a problem which does persist is the so-called land-sea contamination (LSC) effect, an artificial increase of brightness temperature around large land masses that enters into the ocean several hundreds of kilometers. This artifact has been found to be caused by an inconsistency between the multiplicative error that affects the zero baseline (antenna temperature) and the error affecting the rest of baselines (correlations). This inconsistency is related to about 2% measurement overestimation of the correlation efficiency (fringe washing function at the origin) that produces a scene dependent bias in the retrieved brightness temperature [3]. It must be pointed out that correlation efficiency is periodically measured on-board by means of an internal noise injection scheme [4]. Since antenna frequency response is not included in the noise injection loop, this paper is devoted to assess its potential impact in SMOS end-to-end increased correlation loss.

The Soil Moisture and Ocean Salinity (SMOS) radiometer operates within the Earth Exploration Satellite Service passive band at 1400-1427 MHz. Since its launch in November 2009, SMOS images are strongly impacted by radio frequency interference (RFI). So far RFI sources distributed worldwide have been detected. Up to 42% of these RFIs could be suppressed thanks to the co-operation of the National Spectrum Management Authorities. Some of the strongest RFI sources might mask other weaker sources underneath, hence it is expected the total number of RFI detected may increase as strong ones are progressively identified and switched off. Most RFIs are located in Asia and Europe, which together hold ~73% of the active sources and of the strongest interference. The areas affected by RFI may experience either an underestimation in the retrieved values of soil moisture and ocean salinity or data loss, with the associated detrimental impact on the scientific return. ESA and the teams participating in SMOS mission have put in place different strategies to alleviate this RFI situation.

This paper summarizes the rationale for the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission routine calibration plan, including the analysis of the calibration parameter annual variability, and the performances and stability of SMOS images after one year of data. SMOS spends 1.68% of the total observation time in calibration. The instrument performs well within expectations with regard to accuracy and radiometric sensitivity, although spatial ripples are present in SMOS images. Several mechanisms are currently used or under investigation to mitigate this problem. Also, a loss antenna model has recently been introduced to correct for physical temperature-induced effects. This antenna model successfully corrects observed orbital variations, but has difficulties in correcting brightness temperature long-term drifting, as assessed using relatively well-known targets other than the external calibration region-cold space.

The Soil Moisture and Ocean Salinity (SMOS) satellite is strongly affected by radio-frequency interference (RFI). A detection algorithm has been developed to accurately obtain the coordinates of the interfering source emitters from the SMOS images. The results obtained from this detection algorithm are regularly used to locate the on-ground sources of interference. This has allowed the identification and termination of over 200 RFI sources observed by SMOS. In the majority of cases, the accuracy of the coordinates provided was better than 4 km, which is a very important achievement considering that SMOS spatial resolution is larger than 35 km and that the contamination of a single RFI can extend to several thousands of kilometers in some cases.

The SMOS radiometer operates within the Earth Exploration Satellite Service passive band at 1400-1427 MHz. Since its launch in November 2009, SMOS images have been strongly impacted by Radio Frequency Interference (RFI). So far approximately 500 RFI sources distributed worldwide have been detected. Some of the strongest RFI sources might mask other weaker RFI underneath, hence it is expected the total number of RFI detected may increase as strong ones are progressively located and switched off. Most RFIs are located in Asia and Europe, which together hold approximately 80% of the active sources and more than 90% of the strongest interference. The areas affected by RFI may experience either an underestimation in the retrieval values of soil moisture and ocean salinity or data loss, with the associated detrimental impact in the scientific return. ESA and the teams participating in SMOS mission have put in place different strategies to alleviate this RF interference situation.

This paper presents the progress made in the calibration and image reconstruction of the brightness temperature data provided by the SMOS mission of the European Space Agency. This progress has been made thanks to the learning through the accumulation of results since the launch of the satellite. Current performance of the payload on-board SMOS, the MIRAS interferometer, our main findings on its behavior and open lines of investigation are included in this contribution.

This paper presents the algorithm developed by the SMOS team to accurately detect the coordinates of the Radio Frequency Interferences (RFIs) sources observed by SMOS. This information is provided then to the national frequency management authorities, as part of a global strategy to improve the RFI situation in the SMOS data. The algorithm makes use of the large amount of observations from SMOS in order to increase the geo-location accuracy of the on-ground emitters despite SMOS moderate spatial resolution for this specific application. On top of that, some emissions detected from several interferences world-wide are so strong that the secondary side-lobe levels associated to the point-source type of signal are much larger than the expected natural radiation from Earth. In this conditions, the detection of the real location of the emitter becomes an important challenge. This problem is overcome with a set of data filters related to the specificities of SMOS reconstructed images. More than 150 RFIs have been switched off thanks to the information provided by this detection algorithm.

In a synthetic aperture radiometer, the sidelobe level is determined by the shape of the synthetic pattern, which, in turn, depends on the window used to weight the visibility samples. Reduced sidelobes are obtained when the weighted visibility is smooth with no abrupt changes in the entire spatial frequency domain. Since standard 2-D windows have circular symmetry, the sidelobes are reduced if visibility samples are chosen only within a circle. This technique has been successfully tested with Soil Moisture and Ocean Salinity data, demonstrating an important reduction of sidelobes with some degradation of spatial resolution.

In this paper, we present an analysis of the radiometric performance of the three 1.4-GHz noise injection radiometers of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite. The units measure the antenna temperature, which contributes to the average brightness temperature level of SMOS retrievals. We assess the radiometric resolution of the receivers, the similarity between their measurements, and their thermal stability. For these purposes, we use SMOS measurement data gathered during the first year of the orbital operations of the satellite, which was launched in November 2009. The main results from the analysis are that the units meet the design requirements with a margin. Also, we present a new thermal model for the radiometers to further enhance their stability.

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission was launched on the 2nd of November 2009. The first six months after launch, the so-called commissioning phase, were dedicated to test the functionalities of the spacecraft, the instrument, and the ground segment including the data processors. This phase was successfully completed in May 2010, and SMOS has since been in the routine operations phase and providing data products to the science community for over a year. The performance of the instrument has been within specifications. A parallel processing chain has been providing brightness temperatures in near-real time to operational centers, e.g., the European Centre for Medium-Range Weather Forecasts. Data quality has been within specifications; however, radio-frequency interference (RFI) has been detected over large parts of Europe, China, Southern Asia, and the Middle East. Detecting and flagging contaminated observations remains a challenge as well as contacting national authorities to localize and eliminate RFI sources emitting in the protected band. The generation of Level 2 soil moisture and ocean salinity data is an ongoing activity with continuously improved processors. This article will summarize the mission status after one year of operations and present selected first results.

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission is perturbed by radio frequency interferences (RFIs) that jeopardize part of its scientific retrieval in certain areas of the world, particularly over continental areas in Europe, Southern Asia, and the Middle East. Areas affected by RFI might experience data loss or underestimation of soil moisture and ocean salinity retrieval values. To alleviate this situation, the SMOS team has put strategies in place that, one year after launch, have already improved the RFI situation in Europe where half of the sources have been successfully localized and switched off.

The performance requirements of the SMOS payload are demanding in terms of spatial resolution, accuracy, stability and precision, all critical to fulfill its scientific objectives. For this reason a commissioning plan for MIRAS was carefully devised to verify, calibrate and characterize all instrument parameters which could have an impact on its performance. This presentation describes the most important results from the instrument commissioning phase.

The Corbella's revision of the fundamental equation of the interferometric aperture synthesis radiometry is verified using airborne and spaceborne data. This experimental verification uses the measurements of the airborne instrument HUT-2D from the Aalto University (Helsinki), and the unique spaceborne microwave imaging radiometer by aperture synthesis (MIRAS) from the ESA's Soil Moisture and Ocean Salinity (SMOS) mission. The data acquired with those sensors support the Corbella's revision of the visibility function. The revised function predicts that visibilities depend on the contrast between the target's brightness temperature and the backward noise of the receivers emitted through the antennas.