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The Chang E’-1 and E’-2 (CE-1 and CE-2) orbital sounders provided high resolution global maps of lunar microwave brightness temperatures (TB) at wavelengths of 0.8, 1.55, 3.85, and 10 cm covering approximately two years of data over the 2007-2010 time frame. The four channel microwave radiometers (MRMs) effectively sampled the upper ~2 meters of the lunar regolith and are diagnostic of thermal and electrical properties including mineralogy, rock abundance and, potentially, interior heat flow. Early comparisons of co-located data between the two instruments revealed ~10-20 K offsets between the CE-1 and CE-2 measurements that required in-flight recalibration efforts. These have included comparisons with model predictions at Apollo sites as well as adjustments of the cold sky horn reference temperatures to include contamination from lunar surface emissions. This paper proposes an in-flight recalibration methodology that focuses on correction of the pre-flight transfer coefficients that determine the relative importance of component losses along the radiometer hardware paths connecting the antennas to the detectors. It is shown that for each channel a single parameter, representing the ratio of the cold sky and main antenna transfer coefficients, can be constrained by knowledge of the stable regolith physical temperatures below the diurnal-varying layer, and is sufficient to establish values for the complete set of hardware transfer coefficients. The in-flight comparisons proposed for recalibration are based on backside highland models of regolith thermal properties. Potential remaining offsets of the recalibrated MRM data are evaluated in terms of parameter uncertainties of our chosen nominal thermal model.

Across spatial and temporal scales, sea-ice motion has implications on ship navigation, the sea-ice thickness distribution, sea ice export to lower latitudes and re-circulation in the polar seas, among others. Satellite remote sensing is an effective way to monitor sea-ice drift globally and daily, especially using the wide swaths of passive microwave missions. Since the late 1990s, many algorithms and products have been developed for this task. Here, we investigate how processing sea-ice drift vectors from the intersection of individual swaths of the Advanced Microwave Scanning Radiometer 2 (AMSR2) mission compares to today's status-quo (processing from daily averaged maps of brightness temperature). We document that the swath-to-swath (S2S) approach results in many more (two orders of magnitude) sea-ice drift vectors than the daily-maps (DM) approach. These S2S vectors also validate better when compared to trajectories of on-ice drifters. For example, the RMSE of the 24 hour Arctic sea-ice drift is 0.9 km for S2S vectors, and 1.3 km for DM vectors from the 36.5 GHz imagery of AMSR2. Through a series of experiments with actual AMSR2 data and simulated Copernicus Imaging Microwave Radiometer (CIMR) data, we study the impact that geo-location uncertainty and imaging resolution have on the accuracy of the sea-ice drift vectors. We conclude by recommending that a swath-to-swath approach is adopted for the future operational Level-2 sea-ice drift product of the CIMR mission. We outline some potential next steps towards further improving the algorithms, and making the user community ready to fully take advantage of such a product.

Microwave emission is influenced by regolith thermophysical properties that can reveal the geological evolution of the Moon. Lunar near-surface microwave emission has been systematically investigated by the microwave radiometer (MRM) onboard Chinese Chang'E-2 (CE-2) lunar satellite. However, recent work showed that global calibration issues were causing discrepancies between CE-2 observations and theoretical simulations at 3.0- and 7.8-GHz channels, which influences data interpretations and applications. In this study, we use a new method to improve thermal models by employing the bolometric brightness temperature and thermophysical property of subsurface structure derived from high quality and repeated coverage Diviner data. The derived subsurface temperatures make it possible for us to improve the accuracy of microwave brightness temperature (TB) simulation within 70°N/S latitudes. We evaluate the MRM data quantitatively by comparing the global TB between modeled values and CE-2 observations (i.e., offset values) at different local times (LTs) and latitudes. The results show that offset values of the two channels vary significantly with LT, especially near 06:00 and 18:00. However, the 7.8-GHz channel presents greater (~12k in average) calibration uncertainties than the 3.0-GHz channel. In addition, the offset of both the two channels becomes complex at high latitudes but presents an obvious north-south asymmetry. Finally, we modify the MRM data according to different offsets at different LTs and latitudes. The modified global TB maps provide us a new view to characterize the lunar near-surface thermal environment, especially for low-TB spots that are related to the elevated rock abundance and crater degradation.

Temporal Experiment for Storms and Tropical Systems—Demonstration (TEMPEST-D) is a 6U CubeSat satellite with a cross-track scanning millimeter-wave radiometer measuring at five frequencies from 87 to 181 GHz. It employs a direct-detection architecture with InP HEMT monolithic microwave integrated circuit (MMIC) low-noise amplifiers and related new technologies. An end-to-end two-point external calibration is performed every 2-s rotation of the scanning mirror, based on observations of the cosmic microwave background and an internal blackbody calibration target, with three thermistors to monitor the target physical temperature. Corrections for antenna pattern effects and cross-scan biases based on prelaunch measured values were updated using data from an on-orbit calibration pitch maneuver. Validation of the observed brightness temperatures ( $T_{\text {B}}$ ) is performed by comparing to coincident nonprecipitating ocean observations from five well-calibrated on-orbit instruments, including Global Precipitation Measurement (GPM) mission Microwave Imager (GMI) and four Microwave Humidity Sounder (MHS) sensors on board NOAA-19, MetOp-A, MetOp-B, and MetOp-C satellites. Absolute calibration accuracy is within 1 K for all channels, well within the 4-K requirement. Calibration precision, or stability over time, is within 0.6 K for all channels, also well within the 2-K requirement. The intrinsic noise of TEMPEST-D is lower than MHS, resulting in similar on-orbit noise equivalent differential temperatures (NEDTs), even though TEMPEST-D has a much shorter integration time of 5 ms as compared to 18 ms for MHS. As a result, although the TEMPEST-D radiometer is substantially smaller, lower power, and lower cost than similar current operational radiometers, it has comparable or better performance in terms of instrument noise, calibration accuracy, and calibration stability or precision.

Compared with traditional real aperture microwave radiometers, one-dimensional synthetic aperture microwave radiometers have higher spatial resolution. In this paper, we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz, 10.65 GHz, 18.7 GHz and 23.8 GHz at multiple incidence angles. We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature. The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature. Then, a backpropagation (BP) neural network algorithm, a random forest (RF) algorithm and two multiple linear regression algorithms (RE1 and RE2) were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°–65°. The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise. The BP achieves the lowest retrieval errors at all incidence angles. The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.

Sea surface salinity (SSS) in coastal zones with high temporal and spatial resolutions is also needed for scientific research and marine economy. However, one of the limitations of airborne L -band real-aperture microwave radiometers and synthesis aperture interferometric radiometers is high mass and volume or the high complexity of the system. To overcome the limitations, an L -band phased array radiometer is proposed as an alternative solution to monitor SSS in coastal zones from a small unmanned aerial vehicle (UAV). The L -band phased array radiometer is introduced, which only comprises a phased array and a single receiver. In addition, the calibration methods of the L -band phased array, radiometer that the external calibration method and the internal calibration method, are also introduced. A series of experiments was performed to assess the performance of the L -band phased array radiometer. The results indicate that the L -band phased array radiometer show a good performance in low pointing angles and low scanning angles. As a conclusion, the L -band phased array radiometer can be an alternative solution to monitor SSS in coastal zones with high temporal and spatial resolutions from a small UAV.

The MIRS microwave radiometer–spectrometer is described. The instrument is being developed using a conceptual design that was the first stage of ground preparations for the Convergence Space Experiment (SE). At the next stage of SE implementation, it is planned to use the proposed technical solutions as design documentation for manufacturing test and flight prototypes. MIRS is a multi-frequency scanner and sounder intended to record the characteristic radiothermal radiation emitted by the system of the Earth’s surface and atmosphere. The set of frequencies of the received radiation is in the range of 10 to 200 GHz. The device is to be installed on the Russian Orbital Segment (ROS) of the International Space Station (ISS). Conical scanning of the Earth’s surface is done by rotating an antenna unit mounted on a fixed base. With a 1.3 s period of rotation and a constant Earth incidence angle of 53.1 deg, continuous coverage of the Earth’s surface is ensured in a swath 800 km wide with spatial resolution of 10 km for the highest-frequency channels. Nine radiometer–polarimeters laid out as a full-power radiometer are used as radiation receivers. The MIRS antenna system is an offset parabolic antenna with separated irradiators. The optimum design solutions allowing the main problems of the SE to be solved and the MIRS parameters to be maintained under operating conditions on board the ISS are chosen for the conceptual design.

In a traditional spaceborne microwave radiometer system with a scanning antenna there is often a conflict between spatial and radiometric resolution. Integration over many beams per frequency might be necessary to improve radiometric resolution. Many beams may be generated using many classical feed horns or by a Focal Plane Array (FPA) system. At C-band horns are bulky and replacing several such horns with a FPA is an interesting option. The FPA concept uses many small antenna elements, many receivers, and powerful on-line digital processing. A focal plane array system that can replace 4 horns is evaluated, especially concerning power consumption.

形態: 図版あり, Physical characteristics: Original contains illustrations, Accepted: 2020-04-23, 資料番号: PA2110046000

Calibration plays an important role in improving the accuracy of the microwave and millimeter-wave radiometric measurements. Several calibration techniques have been used in radiometers including external calibration targets, vicarious sources, and internal calibrators such as noise diodes or matched reference load. A new calibration technique based on deep learning has recently been developed to calibrate microwave and millimeter-wave radiometers. The deep-learning calibrator has been previously demonstrated on a computer noise-wave modeled Dicke-switching radiometer. This article applies the new deep-learning calibration technique for the calibration of the high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) instrument. A deep-learning neural network model is built to calibrate the 2014 West Coast Flight Campaign antenna temperature measurements of the HAMMR. The deep-learning calibrator antenna temperature estimates are obtained from the radiometric measurements. The deep-learning calibration results are compared with the existing conventional calibration techniques used in HAMMR 2014 field campaign. The results have shown that the deep-learning calibrator is in agreement with the conventional calibration techniques. In this article, it is demonstrated that the deep-learning calibrator can be employed for calibrating the radiometers with high accuracy.

Haiyang-2B (HY-2B) is the second marine dynamic environment satellite of China. Sea surface temperature (SST) products from the scanning microwave radiometer (SMR) onboard HY-2B satellite are evaluated against in situ measurements. Approximately, ten months of data are used for the initial evaluation, from January 15, 2019 to November 15, 2019. The temporal and spatial windows for collocation are 30 min and 25 km, respectively, which produce 450 416 matchup pairs between HY-2B/SMR and in situ SSTs. The statistical comparison of the entire data set shows that the mean bias is −0.13 °C (SMR minus buoy), and the corresponding root-mean-square error (RMSE) is 1.06 °C. Time series of collocations for the SST difference shows that a good agreement is found between HY-2B/SMR and in situ SSTs after June 15, revealing a mean bias and an RMSE of only 0.09 °C and 0.72 °C, respectively. A three-way error analysis is conducted between the SMR, Global Precipitation Measurement Microwave Imager (GMI), and in situ SSTs. Individual standard deviations are found to be 0.41 °C for the GMI SST, 0.15 °C for the in situ SST, and 1.03 °C for the SMR SST. The results indicate that the HY2B/SMR SST products need to be improved during the period from January 15, 2019 to June 15, 2019.

Chinese FY-4M is a new-generation geosynchronous satellite, which will be launched in the near future. It is equipped with multichannel millimeter wave radiometers, which operate in the range of 50–430 GHz. This satellite will increase revisit time and significantly improve the monitoring and weather variation forecasting capabilities. Calibration is an important issue for the quantitative analysis and application of brightness temperature observations. Calibration is first conducted in a thermal/vacuum chamber prior to the launch. A hot target onboard the satellite is used to provide relative irradiance for onboard calibration, and the cold cosmos is used as a cold target. However, complicated space conditions may result in many uncertainties and instabilities during calibration. A new method is required to evaluate the performance of the instruments during long-term operation. Because of the non-existence of atmospheric and other environmental interferences, the lunar surface maintains its physical and chemical stability. Thus, it is an ideal source for thermal calibration. The earliest ground-based observation of thermal microwave emission of the Moon dates back to the early 1940s. At that time, the temperature profile and dielectric constant of the lunar surface had not been studied in detail. Thus, interpreting the observed microwave brightness temperature was difficult. In recent years, many studies of the lunar surface have been performed owing to the advances in satellite-borne remote sensing programs. The Diviner Lunar Radiometer Experiment onboard the Lunar Reconnaissance Orbiter investigated the global solar reflectance and mid-IR irradiance. These infrared measurements contribute to the quantitative description of the thermophysical properties of the superficial lunar regolith media. Chinese probes, Chang’e-1 and Chang’e-2, carried four-channel microwave radiometers to observe the microwave thermal emission of the lunar regolith media, which may provide information on superficial dielectric properties of the lunar surface. These advances created a foundation for the millimeter channel observation of the lunar surface. In this study, a real-time model of the sub-solar position and total irradiance of the lunar surface was developed. The altitude of FY-4M is 35800 km. The distance between the Moon and the Earth is between 363400 km (perigee) and 405400 km (apogee). This large distance enables nadir observation from the FY-4M radiometer toward the center region of the lunar equator. The observation beam angle ranges from 0.097° to 0.027°. The diameters of the observation regions at different channels are 750 km (55 GHz), 480 km (89, 118 GHz), 300 km (166, 183 GHz), and 210 km (425 GHz) at apogee. Based on the surface albedo derived from the Clementine data and the constrained thermophysical parameters of the lunar regolith media obtained from the Diviner infrared brightness temperature, the one-dimensional thermal transfer equation is solved to obtain the physical temperature profile of the lunar regolith media. Using the 37-GHz brightness temperature from Chang’e-2 observations, the loss tangent of the regolith media is inverted. Using the fluctuation dissipation theorem, the brightness temperature of the lunar surface in FY-4M millimeter channels is calculated. The thermophysical profile of the regolith can be validated using the Diviner infrared brightness temperature data. The calculated temperature at a depth of 1.3 m is consistent with the measurements obtained in the Apollo heat flow experiment. The surface temperature and millimeter brightness temperature on the lunar equator (0°N, 0°E) during the entire year of 2010 are simulated. The peak value of the brightness temperature is attained after that of the surface physical temperature peak value. In the low frequency channel, the penetration depth increases, its peak value is typically small, and the peak appears later. This study thus presents an effective model for FY-4M calibration and data analysis.

The high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) is a cross-track scanning airborne radiometer instrument with 25 channels from 18.7 to 183.3 GHz. HAMMR includes: low-frequency microwave channels at 18.7, 23.8, and 34.0 GHz at two linear-orthogonal polarizations; high-frequency millimeter-wave channels at 90, 130 and 168 GHz; and millimeter-wave sounding channels consisting of eight channels near the 118.75 GHz oxygen absorption line for temperature profiling and eight additional channels near the 183.31 GHz water vapor absorption line for water vapor profiling. HAMMR was deployed on a twin otter aircraft for a west coast flight campaign (WCFC) from November 4–17, 2014. During the WCFC, HAMMR collected radiometric observations for more than 53.5 h under diverse atmospheric conditions, including clear sky, scattered and dense clouds, as well as over a variety of surface types, including coastal ocean areas, inland water and land. These measurements provide a comprehensive dataset to validate the instrument.

Microwave radiometers are the key sensors to globally monitor environmental parameters; however, it suffers from its low and nonuniform spatial resolution. In this paper, a superresolution (SR) technique based on image degradation and residual network is proposed to enhance the spatial resolution of microwave radiometer data. Specifically, an improved degradation model is proposed to construct pairs of high-resolution (HR) and low-resolution (LR) data for training and testing. In addition, a new residual network connected by the SR main and gradient auxiliary branches in parallel is designed to achieve SR reconstructions, where eight-channel gradient maps extracted from LR data are input into the auxiliary branch to help to reconstruct. SR results are eventually generated by the trained SR network. Experiments executed on both simulated and actual data demonstrate the soundness and the superiority of the proposed SR technique.

In this paper, a multiband noncontact temperature-measuring microwave radiometer system is developed. The system can passively receive the microwave signal of the core temperature field of the human body without removing the clothes of the measured person. In order to accurately measure the actual temperature of multilayer tissue in human core temperature field, four frequency bands of 4–6 GHz, 8–12 GHz, 12–16 GHz, and 14–18 GHz were selected for multifrequency design according to the internal tissue depth model of human body and the relationship between skin depth and electromagnetic frequency. Used to measure the actual temperature of human epidermis, dermis, and subcutaneous tissue, a small and highly directional multiband angular horn antenna was designed for the radiometer front end. After the error analysis of the full-power microwave radiometer, a novel hardware architecture of the microwave interferometric temperature-measuring radiometer is proposed, and it is proven that the novel interferometric microwave radiometer has less error uncertainty through theoretical deduction. The experimental results show that the maximum detection sensitivity of the novel interferometric microwave temperature-measuring radiometer is 215 mV/dBm, and the temperature sensitivity is 0.047 K/mV. Compared with the scheme of the full-power radiometer, the detection sensitivity is increased 7.45-fold, and the temperature sensitivity is increased 13.89-fold.

The scanning microwave radiometer (RM) onboard the Haiyang-2A (HY-2A) satellite has low-frequency channels with the capability of observing sea surface temperature (SST) from space. To improve the accuracy of the HY-2A RM SST data, the intercalibration of RM brightness temperature (BT) and SST retrieval were carried out. Based on the simulated BTs using the microwave radiative transfer model (RTM), the double-difference approach was applied to perform the intercalibration of RM BTs for the 10.7, 18.7, 23.8, and 37.0 GHz channels, with the Global Precipitation Measurement (GPM) Microwave Imager (GMI) as the reference. The RM 6.6-GHz BTs were corrected with the RTM modeled BT on account of a lack of the similar channel in GMI. The comparison of RM original BTs with GMI and modeled BTs showed large biases and the strong dependence on latitude. We obtained latitude-dependent coefficients using robust linear regression for RM BT correction and applied recalibrated RM BTs for the SST retrieval. The validation of the RM retrieved SST showed the bias of −0.12 °C and the robust standard deviation (RSD) of 1.10 °C compared with buoy SST in the region between 70°S and 70°N. In the tropical and subtropical regions, the bias was −0.12 °C and the RSD was 0.93 °C. In addition, the relationships between the SST difference and the sea surface and atmospheric parameters were investigated. Both statistics of validation results and error analysis indicated significant improvement of RM SST accuracy.

Microwave thermometry provides noninvasive detection of thermal inhomogeneity in biological tissues, early diagnosis of oncological diseases, and correction of treatment based on changes in the parameters of the body’s electromagnetic radiation. We present an analytical review of developments in medical radiometers. Challenges hindering the development of radiometry are identified, as are proposed solutions.

Ground-based microwave radiometers profilers (MWRPs) have been used in numerical weather prediction (NWP) systems and show different impacts on forecasts. Currently, there are around hundreds of ground-based MWPRs used in weather stations over China; however, the application of MWPRs in NWP systems is rather limited. In this work, two MWRP retrieved profiles were assimilated into the Weather Research and Forecasting(WRF) model for a rainstorm event that occurred in Beijing, China. The quality of temperature and humidity profiles retrieved from the MWRP was evaluated against radiosonde observations and showed the reliability of the two MWRP products. Then, comparisons between the measurements of ground-based rain gauges and the corresponding forecasted precipitation in different periods of the rainstorm were investigated. The results showed that assimilating the two MWRPs affected the distribution and intensity of rainfall, especially in the early stage of the rainstorm. With the development of the rainstorm, adding MWRP data showed only a slight influence on the precipitation during the stable and mature period of the rainstorm, since the two MWRP observations were too limited to affect the large area of heavy rainfall.

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.

Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.

Ground-truth experiments are needed to calibrate and validate satellite microwave data and to improve the quality and utilization efficiency of satellite data in solving problems of hydrometeorological support. This paper considers the arrangement of specialized test observatories in the satellite data validation subsystem exemplified by the geophysical observatory in Lehtusi (a town in Leningrad oblast), describes the state and prospects of its equipping with modern tools of contact and remote measurements of meteorological parameters, and indicates directions of scientific research.

Deep learning artificial neural network techniques can be applied for on-orbit calibration of microwave and millimeter-wave radiometer spaceborne instruments, including those for small satellites. The noise-wave model has been employed for noise characterization and validation of the proposed deep learning calibration technique for a synthetically generated Dicke-switching radiometer. The developed deep learning neural network radiometer calibrator produces high accuracy estimates of antenna temperatures from the measurements of radiometer output voltage and thermistor readings. Tests with noise-free and noisy samples of the developed model have shown that the proposed calibration method does not add any significant noise to the radiometer calibration. The performance of the proposed method does not degrade with increased nonlinearity for a radiometer, while nonlinearity is a challenging issue for conventional calibration techniques. The deep learning calibration model learns the radiometer noise characteristics from radiometer prelaunch measurements during thermal vacuum chamber testing. The neural network calibrator proposed in this paper has self-learning capability during the on-orbit operation of a radiometer that can be used to improve the performance of on-orbit calibration. The proposed technique is demonstrated by comparing the residual uncertainty of the deep learning calibration with the theoretical value. No numerical study is presented to compare the performance with conventional calibration techniques. The new method may be solely applied to calibrate the radiometer or applied along with conventional calibration techniques.

Consistency between the brightness temperatures observed with a ground-based microwave radiometer and the brightness temperatures computed by forward modeling is important in many different data applications. Using the National Centers for Environmental Prediction-Final Operational Global Analysis (NCEP-FNL) dataset as a reference, the brightness temperature was obtained through the radiation transfer model for forward calculation. The problem of segmented features in long time of observational data from ground-based microwave radiometers (the so-called “jumping problem”) was identified. By analyzing the deviation and correlation between the observational bright temperature data and the forward calculated data under clear sky conditions, a revised scheme is proposed for the bright temperature observational data. Data obtained with a ground-based microwave radiometer in Beijing from January 1, 2010 to December 31, 2011 around the date of liquid nitrogen calibration show that the correlation between the observed brightness temperatures and the forward computed brightness temperatures is better after correction, especially at 28 and 30 GHz. The “jumping” problem in the observational data for the brightness temperature is eliminated after correction and the time continuity of the observational data and its consistency with the forward calculated data based on the NCEP-FNL dataset are improved. The proposed correction scheme can be used both for real-time data quality control and to improve the accuracy of historical datasets obtained with poorly calibrated microwave radiometers or radiometers working in polluted environments.

Space-borne One-dimensional multifrequency synthetic aperture microwave radiometer (1D-MSAMR) offers new possibilities for detecting high spatial resolution sea surface temperature (SST). To achieve simultaneous observation of multifrequency, we present a spatial resolution calculation model of 1D-MSAMR. Based on this model, the relationship between spatial resolution and antenna parameters are discussed thoroughly in this paper. In addition, we present a set of antenna parameters which can realize the simultaneous observation. The results indicate that the spatial resolution is symmetrical with the change of incidence angle, and the larger the incidence angle, the lower the spatial resolution; the spatial resolution is improved by increasing the minimum antenna spacing, increasing the maximum baseline, or increasing the operating frequency; and to achieve simultaneous observation with multiple frequencies the minimum baseline and the maximum baseline of each frequency need to be consistent. A reasonable antenna parameter scheme for 1D-MSAMR is proposed based on spatial resolution characteristics.

Ground-based multichannel microwave radiometers (GMRs) can observe the atmospheric microwave radiation brightness temperature at K-bands and V-bands and provide atmospheric temperature and humidity profiles with a relatively high temporal resolution. Currently, microwave radiometers are operated in many countries to observe the atmospheric temperature and humidity profiles. However, a theoretical analysis showed that a radiometer can be used to observe solar radiation. In this work, we improved the control algorithm and software of the antenna servo control system of the GMR so that it could track and observe the sun and we use this upgraded GMR to observe solar microwave radiation. During the observation, the GMR accurately tracked the sun and responded to the variation in solar radiation. Furthermore, we studied the feasibility for application of the GMR to measure the absolute brightness temperature (TB) of the sun. The results from the solar observation data at 22.235, 26.235, and 30.000 GHz showed that the GMR could accurately measure the TB of the sun. The derived solar TB measurements were 9950 ± 334, 10,351 ± 370, and 9217 ± 375 K at three frequencies. In a comparison with previous studies, we obtained average percentage deviations of 9.1%, 5.3%, and 4.5% at 22.235, 26.235, and 30.0 GHz, respectively. The results demonstrated that the TB of the sun retrieved from the GMR agreed well with the previous results in the literature. In addition, we also found that the GMR responded to the variation in sunspots and a positive relationship existed between the solar TB and the sunspot number. According to these results, it was demonstrated that the solar observation technique can broaden the field usage of GMR.

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.

We have developed an algorithm for thin ice detection under winter conditions using the Advanced Microwave Scanning Radiometer 2 (AMSR2) radiometer high-frequency brightness temperature (36 and 89 GHz) L1R swath data, and a method to combine thin ice swath charts to a more reliable daily thin ice chart. Moderate Resolution Imaging Spectroradiometer (MODIS) ice thickness swath charts were used as reference data for the algorithm development. The algorithm is based on the classification of 36-GHz polarization ratio (PR36) and H-polarization 89–36-GHz gradient ratio (GR3689H) signatures with linear discriminant analysis. We applied an atmospheric correction to the AMSR2 L1R data following established sea ice concentration (SIC) retrieval algorithms. The PR36 and GR8936H signatures were adjusted to a constant air temperature ( $T_{a}$ ) before the thin ice detection using an empirical relationship between them and $T_{a}$ . The maximum thickness of detected thin ice was estimated to be 20 cm. The thin ice detection with the L1R data is conducted only when SIC $\ge70$ % and $T_{a}\le -5\,\,^\circ \text{C}$ to limit conditions where thick ice may be erroneously detected as thin ice. The thin ice detection algorithm was developed for the Barents and Kara Seas, but it should also be applicable for other Arctic marginal ice zones (MIZs). The daily thin ice chart was validated using an independent set of MODIS daily ice thickness charts. The average probability for misclassification of thick ice as thin ice was 10% and 32% for vice versa. We demonstrate the use of the daily thin ice chart for monitoring the thin ice fraction in the Barents and Kara Seas.

A next-generation real-aperture spaceborne radiometer system for high-quality ocean measurements is discussed. Instead of illuminating the antenna reflector by a classical feed array of horn antennas in a one-feed-per-beam configuration, a multi-feed-per-beam configuration is chosen. Each antenna beam is thus created by adding the outputs from many small antenna elements in the feed array, thus providing an antenna beam of unsurpassed quality. This solves the classical polarization purity and land/sea contamination issues. The concept requires many microwave receivers and fast analog-to-digital converters as well as fast digital signal processing onboard the satellite. This is discussed, and resource budgets, especially concerning power, are provided.

Sea-ice monitoring using long-term data from satellite passive microwave instruments allows one to make quantitative estimates of climatic trends. These numerical estimates depend on the methods used for sea-ice parameter retrievals. This work presents a review of methods to retrieve sea-ice parameters from the data of satellite microwave radiometers. An analysis of the physics of the formation of microwave radiation over sea ice and its transport in the atmosphere makes it possible to determine the main sources of errors and classify methods. This paper considers the basic principles underlying the methods, assumptions, and approximations used and it analyzes the verification data. Weather filters are considered to identify the areas of open water. A comparative analysis of the advantages and limitations of the main sea-ice concentration retrieval methods is provided by measurements of satellite microwave radiometers such as the Radiometers of the Special Sensor Microwave/Imager series (SSM/I) and the Advanced Microwave Scanning Radiometer (AMSR). A review of satellite products based on SSM/I, AMSR-E, and AMSR2 data, as well as available Internet resources with operational and historical sea-ice data, is presented.

When using traditional methods to measure the microwave/millimeter-wave emissivity of small targets, errors arise due to that the antenna's main lobe and side lobe cannot be completely covered by the target. To eliminate the errors exist in traditional measurement methods, this paper first analyzes the main sources of errors and gives the analytical expression of the errors. On this basis, an improved method named voltage method is proposed. To test the effectiveness of the improved method, the horizontal polarization emissivity and the vertical polarization emissivity of a metal plate coat with stealthy nano-materials were measured at different observation angles by voltage method and traditional method, respectively. A dick radiometer working in 35 GHz is used in the experiments. Simultaneously, the accurate emissivities of the target are obtained by standard arch method. The results show that the voltage method improves the measurement accuracy largely compared to the traditional method.

In this paper, the key technology of interferometric microwave thermometer is studied, the research can be applied to the temperature measurement of human body and subcutaneous tissue. This paper proposes a hardware architecture of interferometric microwave thermometer with 2 GHz bandwidth, in which the phase shifter is used to correct phase error and the quadrature demodulator is used to realize autocorrelation detection function. The results show that when input power is 7 dBm, the detection sensitivity can reach 176.54 mV/dBm and the temperature resolution of the microwave radiometer can reach 0.4 K. Correction algorithm is designed to improve the accuracy of temperature measurement. After correction, the phase error is reduced from 40° to 1.4° and when temperature changes 0.1 °C, the voltage value changes obviously. Step-by-step calibration and overall calibration are used to calibrate the device. Inversion algorithm can determine the relationship between physical temperature and output voltage. The mean square error of water temperature inversion by multiple linear regression algorithm is 0.607 and that of BP neural network algorithm is 0.334. The inversion accuracy can be improved by reducing the temperature range. Our work provides a promising realization of accurate, rapid and non-contact detection device of human body temperature.

Increasing attention is being paid to the monitoring of global change, and remote sensing is an important means for acquiring global observation data. Due to the limitations of the orbital altitude, technological level, observation platform stability and design life of artificial satellites, spaceborne Earth observation platforms cannot quickly obtain global data. The Moon-based Earth observation (MEO) platform has unique advantages, including a wide observation range, short revisit period, large viewing angle and spatial resolution, thus, it provides a new observation method for quickly obtaining global Earth observation data. At present, the MEO platform has not yet entered the actual development stage, and the relevant parameters of the microwave sensors have not been determined. In this work, to explore whether a microwave radiometer is suitable for the MEO platform, the land surface temperature (LST) distribution at different times is estimated and the design parameters of the Moon-based microwave radiometer (MBMR) are analyzed based on the LST retrieval. Results show that the antenna aperture size of a Moon-based microwave radiometer is suitable for 120 m, and the bands include 18.7, 23.8, 36.5 and 89.0 GHz, each with horizontal and vertical polarization. Moreover, the optimal value of other parameters, such as the half-power beam width, spatial resolution, integration time of the radiometer system, temperature sensitivity, scan angle and antenna pattern simulations are also determined.

In this paper, we introduce a novel approach to enhance the spatial resolution of single-pass microwave data collected by mesoscale sensors. The proposed rationale is based on an $L^{p}$ -minimization approach with a variable $p$ exponent. The algorithm automatically adapts the $p$ exponent to the region of the image to be reconstructed. This approach allows taking benefit of the advantages of both the regularization in Hilbert ( $p = 2$ ) and Banach ( $1 ) spaces. Experiments are undertaken considering the microwave radiometer and refer to both actual and simulated data collected by the special sensor microwave imager (SSM/I). Results demonstrate the benefits of the proposed method in reconstructing abrupt discontinuities and smooth gradients with respect to conventional approaches in Hilbert or Banach spaces.

The water cycle observation mission (WCOM) will build upon previous L and C band passive microwave soil moisture satellite missions. WCOM will consist of a passive microwave synthetic aperture radiometer operating at L , S , and C bands. The WCOM requirements for passive soil moisture are to estimate soil moisture in the top 5 cm of soil layer with an error less than 0.04 m3/m3, at 15-km resolution and with a 3-day revisit. A new set of algorithms for these multi-frequency platforms will need to be developed for estimating the data products at the desired resolution. To accomplish this, a brightness temperature (TB) downscaling methodology is developed that uses passive S -band TB (30 km) to downscale L -band TB (50 km) and to estimate soil moisture at a 30-km resolution, based on the linear relationships between the passive signals of L band and S band. To test this downscaling method, analysis was performed using PALS data from the Soil Moisture Experiments in 2002 (SMEX02). For this study, 4-km L -band observations were downscaled to 800 m. The root mean square errors between the downscaled TBL at 800 m with the observed TBL at 800 m are 2.63 and 1.60 K for H and V polarizations, respectively. The results also showed that it was possible to use these disaggregated TB to estimate soil moisture to meet the mission requirement of 0.04 m3/m3. These results showed that we can obtain higher resolution soil moisture from the L -band passive TB with a high accuracy ( S -band information.

A low noise, high gain, stable radiometer front-end is presented for non-invasive tissue thermometry using custom designed narrow band low noise amplifiers (LNAs) and band pass filter (BPF) with 1....

Modern microwave radiometers have demonstrated the feasibility of monitoring surface salinity from space and also the need for better accuracy in cold water. Accuracy could be improved by adding measurements at lower frequencies (lower than the measurement at 1.4 GHz currently used) and closer to the peak in sensitivity of brightness temperature to changes in salinity. Proposals to accomplish this have focused on wide bandwidth receivers which include at the low end frequencies close to the peak in sensitivity. This strategy involves trade-offs, some obvious such as radio frequency interference (RFI) when operating outside the protected band at 1.4 GHz and the loss of spatial resolution at lower frequencies. Others stemming from the interdependence of the retrieval of salinity on water temperature and surface roughness are more subtle. The objective of this manuscript is to examine this interdependence and its implications to future wide bandwidth instruments for remote sensing of salinity from space.

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.

Remote sensing for weather applications is gaining its importance for accurate measurement of atmospheric parameters, especially in the higher microwave and millimeter wave frequency ranges. In this work, feasibility study on design of a dual-band passive radiometer has been carried out for humidity and temperature profiling of atmosphere. Non-conventional 20–32 GHz frequency band (we mention it as K-band here) and 50–60 GHz frequency band (V-band) have been used for sensing atmospheric humidity and temperature, respectively. Few practical applications of passive radiometer for temperature and humidity sounding have been investigated through literature survey and a design of dual-band radiometer RF front end for atmospheric profiling has been done. System-level simulation has been carried out in SystemVue and results have been produced.

This paper presents a built-in calibration procedure of a 10-to-20 GHz polarimeter aimed at measuring the I, Q, U Stokes parameters of cosmic microwave background (CMB) radiation. A full-band square waveguide double directional coupler, mounted in the antenna-feed system, is used to inject differently polarized reference waves. A brief description of the polarimetric microwave radiometer and the system calibration injector is also reported. A fully polarimetric calibration is also possible using the designed double directional coupler, although the presented calibration method in this paper is proposed to obtain three of the four Stokes parameters with the introduced microwave receiver, since V parameter is expected to be zero for the CMB radiation. Experimental results are presented for linearly polarized input waves in order to validate the built-in calibration system. The authors would like to thank The Spanish Ministry of Science and Innovation for financial support provided through the grants ESP2015-70646-C2-2-R, ESP2017-83921-C2-2-R and PID2019-110610RB-C22

In passive remote sensing of the earth, the real-aperture microwave radiometer employs a bulky mechanical scanning platform, which greatly increases the mass and volume of the system. Then, the aperture synthesis microwave radiometer has been developed to alleviate the mass and volume of the real-aperture microwave radiometer. However, the aperture synthesis microwave radiometer has a high complexity in signal processing and system due to it being synthesized by many small aperture antennas. To alleviate the mass and volume of the real-aperture microwave radiometer and the high complexity in signal processing and systemo f the aperture synthesis microwave radiometer, a novel microwave radiometer is proposed, which employs frequency scanning antennas and can observe the scene with electronic scanning, not mechanical scanning. The system structure of the novel microwave is introduced and the main specifications are also analyzed, three receiver architectures for the microwave radiometer used frequency scanning antennas are given and discussed. The calibration method is given. Numerical simulations are also performed to assess the performance of the frequency scanning microwave radiometer.

A new methodology has been described in Kilic et al. (Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer, Remote Sensing 2020, 12, 1060, Part 1 of this study) to estimate Sea Ice Concentration (SIC) from satellite passive microwave observations between 6 and 36 GHz. The Ice Concentration Retrieval from the Analysis of Microwaves (IceCREAM) algorithm is based on an optimal estimation, with a simple radiative transfer model derived from satellite observations at 0% and 100% SIC. Observations at low and high frequencies have different spatial resolutions, and a scheme is developed to benefit from the low errors of the low frequencies and the high spatial resolutions of the high frequencies. This effort is specifically designed for the Copernicus Imaging Microwave Radiometer (CIMR) project, equipped with a large deployable antenna to provide a spatial resolution of &sim, 5 km at 18 and 36 GHz, and &sim, 15 km at 6 and 10 GHz. The algorithm is tested with Advanced Microwave Scanning Radiometer 2 (AMSR2) observations, for a clear scene over the north polar region, with collocated Moderate Resolution Imaging Spectroradiometer (MODIS) estimates and the Ocean Sea Ice&mdash, Satellite Application Facilities (OSI SAF) operational products. Several algorithm options are tested, and the study case shows that both high spatial resolution and low errors are obtained with the IceCREAM method. It is also tested for the full polar regions, winter and summer, under clear and cloudy conditions. Our method is globally applicable, without fine-tuning or further weather filtering. The systematic use of all channels from 6 to 36 GHz makes it robust to changes in ice surface conditions and to weather interactions.

An advanced algorithm for atmospheric water vapor column (WVC) retrieval from the Advanced Microwave Scanning Radiometer (AMSR) measurements over the Arctic sea ice (SI) and open ocean waters is presented. The algorithm is built on the physical modeling of the brightness temperature (BT) of the microwave radiation of the SI–open ocean–atmosphere system at the AMSR frequencies and polarizations. The BTs are calculated using a data set of the SI, atmospheric, and oceanic parameters changing in the range of their natural variability in the Arctic, and using the SI microwave emission coefficients varied according to the published experimental data. The inverse operator explores neural networks (NNs), trained on an ensemble of modeled BTs. The algorithm is applied both to the AMSR-E and to the AMSR2 measurement data. Validation of the algorithm is performed with radiosonde (r/s) WVC measurements from the four Arctic coastal stations at different SI conditions during 2014–2017. The results of the application of the new algorithm to satellite radiometer measurements are also compared with the Era-Interim reanalysis WVC, as well as with other satellite WVC products, based on the data of the Moderate Resolution Imaging Spectrometer (MODIS) and on the data of the Advanced Microwave Sounding Unit-B (AMSU-B) for 2008 and 2015. To justify the usage of the Era-Interim WVC as a reference data set for the algorithm accuracy estimation in the Arctic area, Era-Interim WVC is also compared with the r/s WVC measurements.

The Planetary Boundary Layer (PBL) is an important part of the atmosphere that is relevant in different atmospheric fields like pollutant dispersion, and weather forecasting. In this study, we analyze four and five-year datasets of measurements gathered with a ceilometer and a microwave radiometer to study the PBL structure respectively, in the mid-latitude urban area of Granada (Spain). The methodologies applied for the PBL Height (PBLH) detection (gradient method for ceilometer and the combination of parcel method and temperature gradient method for microwave radiometer) provided a description in agreement with the literature about the PBL structure under simple scenarios. Then, the PBLH behavior is characterized by a statistical study of the convective and stable situations, so that the PBLH was obtained from microwave radiometer measurements. The analysis of the PBLH statistical study shows some agreement with other PBLH studies such as daily pattern and yearly cycle, and the discrepancies were explained in terms of distinct latitudes, topography and climate conditions. Finally, it was performed a joint long-term analysis of the residual layer (RL) provided by ceilometer and the stable and convective layer heights determined by microwave radiometer, offering a complete picture of the PBL evolution by synergetic combination of remote sensing techniques. The PBL behavior has been used for explaining the daily cycle of Black Carbon (BC) concentration, used as tracer of the pollutants emissions associated to traffic., Grupo de Física de la Atmósfera (RNM119)

Method for rainfall rate estimation with satellite based microwave radiometer data is proposed. A method to consider the geometric relationship of the observed ice particles and microwave radiometer in the estimation of precipitation is shown, and its validity is shown by comparing it with precipitation radar data on the ground. Observations at high altitudes, such as ice particles, differ greatly in the location of the observation point projected on the ground surface and in the upper troposphere where the observations exist. This effect was insignificant when the precipitation was small because ice particles were often absent, but it was found that the effect was large when the precipitation was large. In other words, the proposed method is effective and effective for Advanced Microwave Scanning Radiometer (AMSR) data in Houston, which was shown as an example of a highly developed convective rain cloud with an In the case of Kwajalein, the effect is insignificant. In addition, the proposed method requires an assumption of ice particle height, and it is necessary to make assumptions based on climatic values. In addition, microwaves in the 89 GHz band, which are considered to be sensitive to ice particles, are not only sensitive to ice particles, so it must be taken into account that they are also affected by the presence of non-ice particles.