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Active and passive microwave characteristics of diurnal soil freeze-thaw transitions and their relationships are crucial for developing retrieval algorithms of the soil liquid water content (θliq) and freeze/thaw state, which, however, have been less explored. This study investigates these microwave characteristics and relationships via analysis of ground-based measurements of brightness temperature (TB) and backscattering coefficients (σ⁰) in combination with simulations performed with the Tor Vergata discrete radiative transfer model. Both an L-band (1.4 GHz) radiometer ELBARA-III and a wide-band (1-10 GHz) scatterometer are installed in a seasonally frozen Tibetan meadow ecosystem to measure diurnal variations of TB and copolarized σ⁰ at both hh (σhh⁰) and vv (σ vv⁰) polarizations. Analysis of measurements collected between December 2017 and March 2018 shows that 1) diurnal cycles are observed in both TB and σ ⁰ due to the change in surface θliq caused by diurnal soil freeze-thaw transitions; 2) a negatively linear relationship is found between e and σ⁰ regardless of frequency, polarization combinations, and observation angles; 3) slopes (β ) of linearly fit equations between eH and σhh⁰ decrease with increasing observation angles of ELBARA-III, while the ones between eV and σvv⁰ increase with increasing observation angles; and 4) correlations between e and σ⁰ increase with decreasing microwave frequency of σ⁰ measurements and ELBARA-III observation angles, and magnitudes of diurnal σ⁰ cycles also increase with decreasing microwave frequency. Moreover, the calibrated Tor Vergata model shows capability to reproduce both diurnal e and σ⁰ variations as well as to quantify their relationships at different frequencies and observation angles.

This article presents a study on the power consumption and performance analysis of a small, portable, and ultra-low power total power L-band radiometer. The article explores two processing architectures: the ZYNQ 7010 and the ARM A8 embedded microprocessor. The processing algorithm based in C++ was tested for different clock frequencies, ADC sampling speeds, and sizes of the ADC buffer. To reduce the power consumption and the algorithm execution time, high-level and system-level optimizations, along with fixed-point Q(16,16) data representation, were applied to the main code running on LINUX Debian V8. In the case with the ZYNQ 7010, the optimizations had no notable impact on reducing power or execution time in comparison with the ARM A8, where significant variations were measured, showing a tradeoff between power consumption and algorithm performance that limits the processing capability and the system flight time. The ZYNQ 7010 runs the algorithm faster, but the power consumption is higher than the ARM A8. Using the fixed-point Q(16,16) implementation reduced the power consumption and the execution time in both architectures. Based on these results, we developed a heuristic methodology to minimize power consumption and increase the performance. Energy consumption savings for the radiometer during 20 min of flight was 48%. The size of the radiometer was reduced to 30 cm × 30 cm × 10 cm, with a weight of 1.36 kg, (3 lb) allowing the system be carried by small drones. The results were validated measuring salinity at two locations in Western Puerto Rico.

With a growing number of different satellite sensors, data fusion offers great potential in many applications. In this work, a convolutional neural network (CNN) architecture is presented for fusing Sentinel-1 synthetic aperture radar (SAR) imagery and the Advanced Microwave Scanning Radiometer 2 (AMSR2) data. The CNN is applied to the prediction of Arctic sea ice for marine navigation and as input to sea ice forecast models. This generic model is specifically well suited for fusing data sources where the ground resolutions of the sensors differ with orders of magnitude, here 35 km $\times62$ km (for AMSR2, 6.9 GHz) compared with the 93 m $\times87$ m (for sentinel-1 IW mode). In this work, two optimization approaches are compared using the categorical cross-entropy error function in the specific application of CNN training on sea ice charts. In the first approach, concentrations are thresholded to be encoded in a standard binary fashion, and in the second approach, concentrations are used as the target probability directly. The second method leads to a significant improvement in $R^{2}$ measured on the prediction of ice concentrations evaluated over the test set. The performance improves both in terms of robustness to noise and alignment with mean concentrations from ice analysts in the validation data, and an $R^{2}$ value of 0.89 is achieved over the independent test set. It can be concluded that CNNs are suitable for multisensor fusion even with sensors that differ in resolutions by large factors, such as in the case of Sentinel-1 SAR and AMSR2.

In sea surface salinity (SSS) retrieval using L-band passive radiometry, radiometer-independent ocean wind speed is needed as auxiliary data. Wind speed data from scatterometer and weather models are commonly used as auxiliary data in satellite SSS missions. This article's overarching goal is to explore the feasibility of incorporating the cyclone global navigation satellite system (CyGNSS) data into the SSS retrieval algorithm of the soil moisture active and passive (SMAP) mission over tropical and subtropical oceans. As a proof-of-concept study, empirical geophysical model functions in the retrieval algorithm are developed using the statistics of collocated SMAP, CyGNSS, and referenced buoys measurements. The SSS accuracy of CyGNSS-incorporated salinity retrieval is investigated against the SMAP SSS data product. Comparisons show that the proposed CyGNSS-incorporated retrieval algorithm improves the SSS accuracy by 0.1∼0.2 psu at low wind speed (

In this contribution, we present a comparison of three digital real-time spectrometers used in passive remote sensing of ozone and other trace gases in the middle atmosphere. During a period of six months, we connected the spectrometers to the same radiometric front-end to perform parallel observations of the ozone emission line at 110.836 GHz. This allowed us to better characterize a bias previously observed on the integrated spectra of the Acqiris AC240, a widely used digital spectrometer which has been used for more than a decade in many operational microwave radiometers. We investigated the bias under different atmospheric conditions and found that it is caused by multiple sources. Nonlinearities in the calibration are responsible for part of the bias, but a larger contribution stems from a second effect in the AC240. Although this error source is still partly unexplained, we found that a simple correction scheme simulating a spectral leakage can be applied to the integrated spectra of the AC240 and worked well on our range of observations. We also show that by applying our bias correction to the spectra, we can correct the bias in the ozone retrievals. There is still a need for further measurements to validate this approximate correction, but it could help to correct the numerous time series of ozone and other atmospheric constituents recorded by the AC240.

Fresh water is considered to be one of the most precious natural resources in many countries. Given that soil moisture plays a salient role in vegetation growth, the continuous and timely measurement of soil moisture content is critical to manage water shortages, especially in the agriculture sector [1], [2], which is the largest water use sector in Australia. A 10% water savings in the Australian agriculture sector would be equivalent to a reduction of more than 30% of the combined water consumption from Australian capital cities [3]. Further, soil moisture influences the process of rainfall being partitioned into runoff and infiltration, and saturated soil could turn heavy rain into floods. Therefore, soil moisture information is essential for accurate climate forecasting as well as improving flood and drought prediction [3]-[5].

To monitor sea surface salinity (SSS) in coastal zones with high temporal and spatial resolution, an L-band phased array radiometer is developed. However, it is well known that the L-band radiometers suffer from serious radio frequency interference (RFI) effects. To mitigate the RFI effects, an RFI detection and mitigation algorithm is proposed for the L-band phased array radiometer. The experiments in coastal zones are performed to assess the performance of the RFI algorithm. The results indicate that the detection and mitigation algorithm exhibits good performance and can effectively mitigate the RFI effects.

Objective : Near-field microwave radiometry has emerged as a tool for real-time passive monitoring of local brain activation, possibly attributed to local changes in blood flow that correspond to temperature and/or conductivity changes. The aim of this study is to design and evaluate a prototype system based on microwave radiometry intended to detect local changes of temperature and conductivity in depth in brain tissues. A novel radiometric system that comprises a four port total power Dicke-switch sensitive receiver that operates at 1.5 GHz has been developed. Methods and Results : The efficacy of the system was assessed through simulation and experiment on brain tissue mimicking phantoms under different setup conditions, where temperature and conductivity changes were accurately detected. In order to validate the radiometer's capability to sense low power signals occurring spontaneously from regions in the human brain, the somatosensory cortices of one volunteer were measured under pain-inducing psychophysiological conditions. The promising results from the initial in vivo measurements prove the system's potential for more extensive investigative trials. Conclusion and Significance : The significance of this study lies on the development of a compact and sensitive radiometer for totally passive monitoring of local brain activation as a potential complementary tool for contributing to the research effort for investigating brain functionality.

The Cubesat Radiometer Radio frequency interference Technology validation mission (CubeRRT) was developed to demonstrate real-time on-board detection and filtering of radio frequency interference (RFI) for wide bandwidth microwave radiometers. CubeRRT’s key technology is its radiometer digital backend (RDB) that is capable of measuring an instantaneous bandwidth of 1 GHz and of filtering the input signal into an estimated total power with and without RFI contributions. CubeRRT’s on-board RFI processing capability dramatically reduces the volume of data that must be downlinked to the ground and eliminates the need for ground-based RFI processing. RFI detection is performed by resolving the input bandwidth into 128 frequency sub-channels, with the kurtosis of each sub-channel and the variations in power across frequency used to detect non-thermal contributions. RFI filtering is performed by removing corrupted frequency sub-channels prior to the computation of the total channel power. The 1 GHz bandwidth input signals processed by the RDB are obtained from the payload’s antenna (ANT) and radiometer front end (RFE) subsystems that are capable of tuning across RF center frequencies from 6 to 40 GHz. The CubeRRT payload was installed into a 6U spacecraft bus provided by Blue Canyon Technologies that provides spacecraft power, communications, data management, and navigation functions. The design, development, integration and test, and on-orbit operations of CubeRRT are described in this paper. The spacecraft was delivered on March 22nd, 2018 for launch to the International Space Station (ISS) on May 21st, 2018. Since its deployment from the ISS on July 13th, 2018, the CubeRRT RDB has completed more than 5000 hours of operation successfully, validating its robustness as an RFI processor. Although CubeRRT’s RFE subsystem ceased operating on September 8th, 2018, causing the RDB input thereafter to consist only of internally generated noise, CubeRRT’s key RDB technology continues to operate without issue and has demonstrated its capabilities as a valuable subsystem for future radiometry missions.

In this paper, the problem of detecting radio frequency interference (RFI) in microwave radiometry is addressed. Due to the significant increase in the RFI in natural emissions, an accurate detection method is crucial to retrieve the actual passive sensing measurements. To address this problem, we have proposed a density-based clustering approach that considers both RFI-free and RFI-contaminated radiometer measurements are from different distributions. Further, we have automated the proposed algorithm such that the parameters required for this approach can be extracted from any given data. The evaluation results on simulated data demonstrate improvement over existing RFI detection techniques even in low interference to noise ratio (INR) and low duty cycle (DC) RFI cases.

Recent lunar observations have concluded that significant water ice deposits may exists in the regolith, especially in the permanently shadowed regions near the lunar poles. Detection and utilization of these reserves is very important to sustain the continuous human presence on the Moon. This paper, using analytical models and numerical simulations, demonstrates that wideband microwave radiometers are promising instruments for exploring underground water ice deposits on the Moon as their brightness temperature spectra are highly sensitive to water presence in the regolith.

Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been approved to be taken onbord the Chinese Ocean Salinity Mission. The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). Since radio frequency interference (RFI) is reported as a serious threat to L-band radiometry, the RFI detection and mitigation techniques must be carefully designed before launch. However, these techniques need to be developed based on the knowledge of how RFI affects complex correlation, visibility function, and reconstructed brightness temperature. This paper presents a time-domain signal modeling method for the simulation of interferometric measurement under RFI’s presences, and a simulation system for L-Rad is established accordingly. Several RFI cases are simulated with different RFI types, parameters, and positions, and the RFI characteristics upon L-Rad’s measurement are discussed. The proposed simulation system will be further dedicated to the design of RFI processing strategy onboard MICAP.

Sea ice thickness and salinity are important quantities in understanding and forecasting the evolution of the cryosphere. However, the retrieval of multiple sea ice parameters through microwave remote sensing is a challenging task. In this study, the potential advantages of using a multi-channel wideband microwave radiometer are demonstrated through simulations of the retrieval of both sea ice thickness and salinity for multiple ice types and for different numbers of radiometer channels.

Modern multi-band radiometer imagers are designed trading spatial resolution, spectral coverage, and surface sampling characteristics to optimize science return. In this process, trades must be made to usually under-sample the Earth scene. Care is taken to obtain contiguous 3-dB edge-to-edge coverage, but even so, such a design still aliases high spatial frequency content in the image.

Sun-tracking microwave radiometry (STMW) is a ground-based technique where the Sun is used as a beacon source to infer the atmospheric path attenuation in all-weather conditions. STMW shows an appealing potential for overcoming the difficulties to perform satellite-to-Earth radiopropagation experiments in the unexplored millimeterwave and submillimeter-wave frequency region, especially where experimental data from a beacon receiver are not available. The theoretical framework and the ad hoc procedures and data processing developed in the last 5 years will be presented, together with the estimate of the overall error budget. The application and experimental challenges during long-term deployments, such as the field campaign of the W-band radiometric study (WRad) funded by the European Space Agency (ESA), will be reviewed.

The Soil Moisture Active/Passive satellite was launched in 2015 to provide global and continuous maps of land surface soil moisture and freeze-thaw using L-Band microwave radiometry. Even though the 1400-1427 MHz frequency used by SMAP is a protected portion of the spectrum, Radio Frequency Interference (RFI) is still observed that can corrupt the radiometer's measurements. Nine distinct algorithms are implemented as part of SMAP's level 1 processing to detect and filter out RFI contributions. However, any remaining undetected RFI are major concern especially at the locations of cal/val sites used for evaluating soil moisture retrieval performance. This paper presents an analysis of the RFI environment at SMAP cal/val site locations and assesses the impact of RFI on soil moisture retrievals at those locations.

A new configuration of a pseudo-correlation type radiometer is proposed for a microwave biomedical application, such as diabetic foot neuropathy. The new approach as well as its simulated performance are thoroughly assessed using commercial off-the-shelf components and custom designed subsystems. We configured a pseudo-correlation receiver, centred at 3.5 GHz, to validate the proposal, comparing its simulated response with a measured alternative based on a 90∘ hybrid coupler pseudo-correlation prototype. We custom designed a balanced Wilkinson power divider and a 180∘ hybrid coupler to fulfil the receiver’s requirements. The proposed configuration demonstrated an improved noise temperature response. The main advantage is to enable the recalibration of the receiver through simultaneous measurable output signals, proportional to each input signal, as well as the correlated response between them.

The airborne Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) has participated in the Global Precipitation Measurement (GPM) Olympic Mountains Experiment (OLYMPEX) from November to December, 2015, with great success. With similar channels as that of the GPM Microwave Imager (GMI) at 89–183 GHz, CoSMIR served as a proxy for GMI by flying onboard the DC-8 Aircraft for a total of 17 science flights, collecting over 72 h of observations. The high-quality, calibrated brightness temperature data set is the result of several improvements made to CoSMIR prior to OLYMPEX to make the instrument more reliable. This paper describes these improvements and gives a detailed summary of the CoSMIR measurements obtained from OLYMPEX. CoSMIR experienced minor performance issues during the campaign, most of them were not excessive and only resulted in a loss of approximately 4 h of data for the entire campaign. Performance issues are discussed and shown how they were mitigated to achieve a quality data set. Comparisons of CoSMIR and GMI observations are presented to show that the CoSMIR measurements agree well with GMI. The CoSMIR data set is publicly available as a part of the OLYMPEX data suite and can reliably be used in the GPM algorithm development and related studies.

In order to keep up with the demand for new services, future satellite-to-ground communications will operate at higher frequencies, notably in the 20–50 GHz bands. Consequently, new challenges arise for system designers as the attenuation of the signal crossing the troposphere increases with frequency. Propagation experiments, such as the on-going Alphasat campaign, provide direct measurements of the attenuation. However, other data sources, such as collocated radiometers, are needed to recover the attenuation in nonrainy conditions. This paper uses the Weather Research and Forecasting (WRF) software and investigates Numerical Weather Prediction (NWP) models as an alternative source of nonrainy attenuation time series. Four months of measured Alphasat and radiometric signals collected at Spino d’Adda serve as the reference to assess the accuracy of NWP-derived attenuation. The best agreement between the NWP-derived and the radiometric nonrainy attenuations is achieved with the Tiedtke cumulus scheme. Considering the limits in accuracy inherent to the propagation and radiometric data, the resulting total attenuation statistics are acceptable. The results are expected to improve further with NWP simulation domains closer to the state of the art.

The possibility of detecting oil films on a water surface using passive radar, i.e., microwave radiometers, is considered. Current and prospective microwave radiometric systems that function in different ranges of wavelengths are described. The main technical characteristics of existing radiometric systems are presented. It is shown that the method of microwave radiometry may be used to detect oil films on a water surface.

The influence of tissue compression and external thermal modulation on passive detection of breast tumors using medical microwave radiometry was investigated using multi-physics numerical modeling. A three-dimensional numerical model of the pendant breast with 10 and 6 mm diameter tumors at varying depths (15 mm, 30 mm) was analyzed at thermodynamic equilibrium using a circular waveguide as the receive antenna. The contrast in the brightness temperature, ΔTB , between the unhealthy and healthy breasts was found to be significantly more for breast compression alone, compared to thermal modulation of the tissue surface, irrespective of tissue composition, tumor size, and depth. The study also concludes that small deep-seated tumor with very low metabolic activity that is not detectable by a radiometer with 0.1 °C sensitivity could be detected under breast compression and short duration cold stress. Thus, detection of deep-seated breast tumors can be significantly improved under controlled tissue compression with an optional cold stress. Bioelectromagnetics. © 2019 Bioelectromagnetics Society.

A novel mission concept applying satellite formation flight to passive microwave interferometry was recently proposed to significantly improve the interferometer’s spatial resolution. This concept was shown to sample the visibility in a hexagonal tile of polar grids, and to recover the brightness map, this visibility must be inverted via a discrete polar inverse Fourier transform. For a fast and accurate solution, this letter develops a modified hexagonal variant of the pseudo-polar fast Fourier transform (PPFFT) and its inverse and explores its performance when applied to the proposed formation-flight radiometer. Compared to the conventional rectangular PPFFT, we find approximately a fivefold improvement in the recovered radiometric accuracy, where the rms radiometric error is in the order of $10^{-2}$ K. The impact of visibility interpolation method is also explored, showing that an FFT-based interpolation technique leads to the most accurate final image recovery.

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for $\sigma _{\mathrm{ HH}}^{o} $ , $\sigma _{\mathrm{ VV}}^{o} $ , $T_{\mathrm {BH}}$ , and $T_{\mathrm {BV}}$ , respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data.

The physical basis of microwave radiometry and the construction and technical characteristics of different types of antenna applicators used in medical radiometers are discussed. We present results obtained during the development and the potential uses of new types of antenna applicators in different areas of medicine.

The ultrawideband software-defined microwave radiometer is a 500–2000-MHz radiometer developed to probe temperatures inside ice sheets. Given the instrument’s operation outside of protected portions of the spectrum, radio frequency interference (RFI) is a significant concern, and the instrument is designed to facilitate RFI detection and filtering. This paper analyzes the design and operation of the radiometer, the accuracy and stability of the brightness temperatures it produces, and the RFI analyses of the results acquired in its debut flight over northern Canada and Greenland in September 2016.

The National Aeronautics and Space Administration&rsquo, s (NASA&rsquo, s) Soil Moisture Active&ndash, Passive (SMAP) radiometer has been providing geolocated power moments measured within a 24 MHz band in the protected portion of L-band, i.e., 1400&ndash, 1424 MHz, with 1.2 ms and 1.5 MHz time and frequency resolutions, as its Level 1A data. This paper presents important spectral and temporal properties of the radio frequency interference (RFI) in the protected portion of L-band using SMAP Level 1A data. Maximum and average bandwidth and duration of RFI signals, average RFI-free spectrum availability, and variations in such properties between ascending and descending satellite orbits have been reported across the world. The average bandwidth and duration of individual RFI sources have been found to be usually less than 4.5 MHz and 4.8 ms, and the average RFI-free spectrum is larger than 20 MHz in most regions with exceptions over the Middle East and Central and Eastern Asia. It has also been shown that, the bandwidth and duration of RFI signals can vary as much as 10 MHz and 10 ms, respectively, between ascending and descending orbits over certain locations. Furthermore, to identify frequencies susceptible to RFI contamination in the protected portion of L-band, observed RFI signals have been assigned to individual 1.5 MHz SMAP channels according to their frequencies. It has been demonstrated that, contrary to common perception, the center of the protected portion can be as RFI contaminated as its edges. Finally, there have been no significant correlations noted among different RFI properties such as amplitude, bandwidth, and duration within the 1400&ndash, 1424 MHz band.

Incidence angle diversity of space-borne L-band radiometers needs to be taken into account for a consistent estimation of surface soil moisture (SM). In this study, the Land Parameter Retrieval Model (LPRM) is applied to SMOS brightness temperatures to calibrate the effective scattering albedo (w) and the soil roughness (h 1 ) parameter against ERA5-land SM. The analysis is carried out for SMOS data at three different incidence angles ( 32.5±5∘, 42.5±5∘ and 52.5±5∘ ) focusing in 2016 on the three main land cover types of the Iberian Peninsula according to the Climate Change Initiative (agricultural, forest and grassland). The parameterization shows an increasing trend of w and h 1 with rise of incidence angle. The SM retrieval have been evaluated with in situ SM measurements of the REMEDHUS network on rainfed crop fields. Both compare well at the three incidence angles, obtaining high correlations (0.81-0.85), an ubRMSE around 0.04 m 3 m −3 and low bias (0-0.015 m 3 m −3), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

The calibration strategy for synthetic aperture interferometric radiometers based on noise injection has been successfully demonstrated in the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument onboard the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA). With the emerging demands of increasing both array size and frequency bands, the internal calibration hardware becomes more difficult to implement. Although several external calibration methods have been proposed, the so-called phase ambiguity problem was not carefully considered. In this article, a novel calibration strategy for both phase and amplitude calibrations based on redundant space calibration is proposed, which utilizes the unique structure of equispaced circular array and rotational sampling strategy. The original irregular phase ambiguity degenerates to the fixed p-ambiguity, where only two possible solutions to phases are introduced. Both phase and amplitude of visibility can be simultaneously calibrated by the proposed strategy, and no cooperative calibration target is needed. NSSC’s contribution was supported by the National Natural Science Foundation of China under Grant 41675035, the special Fund for Chinese Meteorological Research in the Public Interest under Grant GYHY201506023, and Beijing Science Project under Grant Z161100002616033. UPC’s contri-bution was supported by the Spanish Ministry of Science, Innovation and Universities, “SPOT: Sensing with Pioneering Opportunistic Techniques”, Grant RTI2018-099008-B-C21/AEI/10.13039/501100011033.

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