Microwave Interferometric Radiometer Research Articles

Lightweight Fan-Beam Microstrip Grid Antenna for Airborne Microwave Interferometric Radiometer Applications.

The microwave interferometric radiometer (MIR) uses aperture synthesis technology to equate multiple small-aperture antennas into a large-aperture antenna to improve spatial resolution. At present, MIR antennas that operate at frequencies above the C-band mostly use horn antennas, waveguide slot antennas, etc., which have the disadvantages of a high profile and large mass. In this paper, a new type of miniaturized, low-profile, and lightweight K-band fan-beam microstrip grid antenna is designed for the airborne campaign of the K-band one-dimensional MIR of a Microwave Imager Combined Active and Passive (MICAP) onboard a Chinese Ocean Salinity Mission (COSM). With a limited size constraint (12.33 mm) on the antenna width, a fan-beam shape antenna pattern was achieved with a 5.34° 3-dB beamwidth in the narrow beam direction and up to a 55° 3-dB beamwidth in the fan-beam direction. A periodic structural unit is proposed in this paper to reduce the design complexity of Taylor weighting, achieving desirable performances on gain (19.1 dB) and sidelobe level (<-20 dB) in the H-plane. Four antenna elements were fabricated and arranged in a non-redundant sparse array. The performance of the four-element sparse array was evaluated with a simulation and real measurement in an anechoic chamber. The coupling between antenna elements was less than -25 dB, and the consistency of phase patterns was better than 3.4°. These results verify the feasibility of the proposed K-band microstrip grid antenna for airborne MIR applications.

Deep Learning Imaging for 1-D Aperture Synthesis Radiometers

For one-dimensional aperture synthesis (1-D AS) radiometers, truncated sampling occurs in the frequency domain due to the system baseline limitation. Therefore, there is an obvious Gibbs oscillation in the reconstructed image. To solve this problem, an imaging method based on a one-dimensional convolutional neural network (1-D CNN) is proposed in this paper. Compared with deep learning methods based on two-dimensional convolutions, the 1-D convolution not only reduces the amount of computation but also produces further performance improvements. The input data of the network are the 1-D visibility function samples, and the output data are the 1-D brightness temperature (BT) samples. The network learns the mapping relationship from the training of the 1-D visibility function samples and 1-D BT samples to complete 1-D AS imaging without any prior knowledge. To verify the performance of this imaging method, simulations and experiments based on the airborne C-band one-dimensional microwave interferometric radiometer (ACMIR) system are implemented. The simulation and experimental results demonstrate that the proposed AS-CNN method achieves higher performance than the IFFT method in terms of image quality and Gibbs phenomenon suppression. In the case of an antenna failure and missing baseline, the AS-CNN method proposed in this paper can still obtain a BT image with high imaging quality, which shows that the robustness of the network is better than that of the IFFT method.

An Airborne C-Band One-Dimensional Microwave Interferometric Radiometer With Ocean Aviation Experimental Results

The medium- and large- scale global sea surface temperature (SSTs), which is an important ocean parameter, are mainly measured by the space-borne microwave radiometry. However, the resolution and sensitivity are greatly limited by antenna size, orbit altitude, and flight speed. In this paper, an airborne C-band one-dimensional (1-D) microwave interferometric radiometer (ACMIR) is developed to obtain the SSTs with a high resolution and sensitivity. The spatial resolution of the ACMIR ranges from 40.7m to 612m, corresponding to the flight height of 500m to 8000m, while the sensitivity varies from 0.25K to 0.36K, associating with the boresight to the edge of the field of view. In order to evaluate the performance of the ACMIR, an ocean aviation experiment was conducted in the coastal area of the Yellow Sea in September 2020. The land observation results indicate that typical ground objects can be clearly distinguished. Furthermore, thesea surface brightness temperatures acquired by the ACMIR are compared with the estimates based on the radiative transfer model, with SST retrieval error of 0.77°C. The ACMIR can offer a high-resolution and accuracy of SST especially in coastal areas, and can meet several application requirements related to SSTs.

A Matrix Completion Based Method for RFI Source Localization in Microwave Interferometric Radiometry

The Soil Moisture and Ocean Salinity (SMOS) mission led by the European Space Agency (ESA) is aimed to globally monitor the Earth surface moisture and ocean salinity. As the single payload of SMOS satellite, the Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) operates in the protected L-band. Nonetheless, the artificial sources emitting close to or/and fully in this band are contaminating the collected remote sensing data and deteriorating the performance of the SMOS mission. Identifying and localizing such sources is crucial to improve the quality of SMOS scientific products. In this article, we propose a method based on matrix completion (MC) for localization of radio frequency interference (RFI) sources. This method mainly exploits the low-rank property of the augmented covariance matrix (ACM) of the sparse array and addresses the ACM incompleteness (i.e., sampling data loss) due to inherent array geometry (e.g., the SMOS Y-shaped array) or potential hardware malfunction (e.g., the correlator failure). Validation results show that, compared with existing RFI localization approaches such as the discrete Fourier transformation (DFT) inversion and covariance-based direction-of-arrival (DOA) estimation, the proposed MC method possesses competitive localization accuracy, superior spatial resolution, and reduced artifacts.

RFI Source Localization in Microwave Interferometric Radiometry: A Sparse Signal Reconstruction Perspective

The Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) is the payload of the Soil Moisture and Ocean Salinity (SMOS) satellite mission led by the European Space Agency. Although the MIRAS operates at the protected L-band, it is perturbed by radio frequency interferences (RFIs) that contaminate the acquired remote sensing data and further deteriorate the total performance of SMOS mission. Accurate location information of these sources is crucial for switching off illegal RFI emitters or mitigating RFI impacts from contaminated data. This article addresses the localization of SMOS RFI sources from a perspective of sparse signal reconstruction (SSR), which exploits the sparsity of RFI sources in the spatial domain. Such an SSR strategy possesses superior (at least comparable) performances over existing RFI localization methods [e.g., discrete Fourier transformation (DFT) inversion and subspace-based direction-of-arrival (DOA) estimation] using only SMOS measurements and even under situations in the presence of data missing due to correlator failures.

An FFT-Based CLEAN Deconvolution Method for Interferometric Microwave Radiometers With Spatially Variable Beam Pattern

A modification to the extended CLEAN deconvolution method for passive microwave interferometric radiometers is presented to account for the interferometer beam patterns that vary depending on the source position within the interferometer field of view. This method is developed for the newly proposed multisatellite rotating microwave interferometric radiometer concept for geostationary atmospheric sounding, which is found to have a spatially varying beam pattern. The proposed method is implemented by the piecewise application of Fast Fourier Transform (FFT)-based convolution, i.e., the image is divided into discrete segments, where the beam pattern is assumed to be constant within each segment. This approach allows the proposed method to exploit the speed advantage of the FFT. Applying this method to the proposed multisatellite interferometer shows a twofold improvement in the radiometric accuracy of the restored brightness temperature map, as compared with the constant beam pattern CLEAN.

Wide Field of View Microwave Interferometric Radiometer Imaging

In microwave interferometric radiometers with a large field of view, as for example the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, one of the major causes of reconstruction error is the contribution to the visibility of the brightness temperature outside the fundamental period, defined on the basis of reciprocal grids. A mitigation method consisting of estimating this contribution through the application of a brightness temperature model outside the fundamental period is proposed. The main advantage is that it does not require any a posteriori addition of artificial scenes to the reconstructed image. Additionally, a method to avoid the sophisticated matrix regularization and inversion techniques usually applied in microwave interferometry is presented. Image reconstruction algorithms are implemented on a minimum grid size in order to maximize their numerical efficiency. An improved method to apply an apodization window to the reconstructed image for reducing Gibbs oscillations is also proposed. All procedures are generally described considering the single polarization case and successively implemented applying the MIRAS layout in both its single polarization and full polarimetric modes. Results show similar performance of the proposed algorithm with respect to the nominal one applied by SMOS. All algorithms are implemented in the MIRAS Testing Software and have been successfully used for scientific studies by other teams.

Preliminary Analysis of the Potential and Limitations of MICAP for the Retrieval of Sea Surface Salinity

A new payload concept has been proposed: the microwave imager combined active/passive (MICAP). MICAP is a combined one-dimensional microwave interferometric radiometer that operates at 1.4, 6.9, 18.7, and 23.8 GHz and L-band (1.26 GHz) scatterometer. It has the capability to simultaneously remotely sense sea surface salinity (SSS), sea surface temperature (SST), and wind speed. MICAP will be a candidate payload onboard the Ocean Salinity Satellite led by the State Oceanic Administration of China to monitor SSS and reduce geophysical errors caused by surface roughness and SST. To provide an “all-weather” estimation of SSS with high accuracy from space, the errors of the simultaneous retrieval of multiparameters using MICAP are analyzed, and noise levels and stability requirements of instruments are estimated. Preliminary analysis shows that MICAP can provide SSS with an accuracy of 1 psu for single measurement and 0.1 psu over the global ocean for 200 × 200 km resolution pixels and one month at middle and low latitudes with default instrument noises (0.1 K, 0.3 K and 0.3 K for the L, C, and K band radiometers, respectively, and 0.1 dB for the L-band scatterometer) while uncertainties of the drift corrections are less than the radiometer sensitivities.

CSMIR: An L-Band Clock Scan Microwave Interferometric Radiometer

Clock scan microwave interferometric radiometer (CSMIR) is a new concept of synthetic aperture radiometer. It has the potentials of being applied to the future Solar Polar Orbit and Geostationary Earth Orbit missions due to the advantages of having a simple and deployable array structure, easy calibration, and flexible visibility sampling. This paper discusses the development of an L-band CSMIR prototype, presents the achievements in hardware design, calibration method, and overall performance tests through outdoor experiments. The experimental results demonstrate the effectiveness of this new concept although some systematic errors and imperfections still exist. Some lessons learned from this prototype are discussed which are helpful to improve the performance in the future.

Performance Analysis of Circular Antenna Array for Microwave Interferometric Radiometers

The microwave interferometric radiometer (MIR) is a passive sensor using synthetic aperture technique for microwave remote sensing. It uses a thinned antenna array to replace the traditional large real aperture antenna, so as to reduce the antenna size, weight, and manufacturing difficulty, and further increase the spatial resolution of the instrument. The antenna array configuration is the first concern for the MIR application. Various array configurations have been proposed. Among them the arrays with hexagonal sampling grid such as the Y-shaped and hexagonal arrays have drawn more attention because of the higher sampling efficiency. However, they do not have the best performance in radiometric sensitivity and radio frequency interference (RFI) mitigation. This paper presents the detailed analysis of the circular array performance and compares it with the Y-shaped and hexagonal arrays. Based on the early developed theory about the radiometric resolution, two new factors named as sampling sensitivity factor and uncertainty factor are first introduced and defined in this paper, which can be used to quantitatively characterize the array performance. The main beam efficiency of the MIR is also redefined to prevent it being uncomfortably greater than unity but still keep a physical significance. Numerical simulations with analysis are finally implemented to verify the theoretical results and also to demonstrate the superiority of the circular array in terms of radiometric sensitivity and RFI mitigation.

Simulation of Microwave Interferometric Radiometer System based on Simulink

Simulation of Microwave Interferometric Radiometer System based on Simulink

Clock Scanning Microwave Interferometric Radiometer and Potential Application Analysis

Microwave (MW) radiometers at low-frequency bands play unreplaceable roles in Earth remote sensing, especially in the areas of numerical weather prediction (NWP) and climate research. All MW radiometers have been flown, so far, at low Earth orbit (LEO), which provide relatively narrow swath with long revisit time. There are increasing demands for applying MW radiometer at geostationary Earth orbit (GEO) for the purpose of having temporally continuous and spatially large coverage. Unfortunately, the required ground spatial resolution leads to a large-sized antenna that prevents MW radiometer applications, especially at low-frequency bands. The new concept of clock scanning microwave interferometric radiometer (CS-MIR) provides an opportunity to resolve this problem. By virtue of the simple and deployable array structure, it has the potential to work at GEO and produce hourly hemispheric imagery. This paper investigates the essential theory of CS-MIR and presents some approaches about its design principles in aspects of array configuration, sampling patterns, polarization corrections, and image reconstruction. The potential GEO applications of CS-MIR in frequencies lower than 50 GHz are investigated. Finally, a conceptual design of CS-MIR for SST measurement from GEO and the associated numerical simulations of image reconstruction are presented.

Imaging Analysis and First Results of the Geostationary Interferometric Microwave Sounder Demonstrator

The Geostationary Interferometric Microwave Sounder (GIMS) is a new concept of atmospheric microwave sounder for China's future geostationary Earth orbit meteorological satellite (FY-4). It is a microwave interferometric radiometer (MIR) using aperture synthesis and working in rotating time-sharing mode with a circular antenna array. A GIMS proof-of-concept demonstrator operating in the temperature sounding bands of 50-56 GHz has been successfully developed. The instrument uses a circular array with 28 elements (including one in the center of the array). It is capable of imaging a scene with an angular resolution of about 0.08. and a radiometric resolution of less than 1 K with 5-m integration time within a 5. field of view (FOV). Some theoretical aspects of the imaging characteristics of GIMS are discussed, such as the alias-free FOV, angular resolution, radiometric resolution, and imaging algorithm. Some early tests and preliminary imaging experiments of the GIMS demonstrator are also presented.

New total electron content retrieval improves SMOS sea surface salinity

AbstractThe European Space Agency (ESA)‐led SMOS (Soil Moisture and Ocean Salinity) mission aims at monitoring both soil moisture (SM) and ocean surface salinity (OS) on a global scale. The SMOS instrument is a microwave interferometric radiometer, which provides visibilities, from which brightness temperatures (TB) maps are reconstructed in the spacecraft' antenna reference frame. In this study, we investigate how to improve the retrieval of salinity thanks to a better knowledge of the ionospheric total electron content (TEC). We show how both the SMOS bias correction (the so‐called Ocean Target Transformation, OTT) and the half orbit TEC profile can be obtained from SMOS third Stokes parameter A3 using a location on the SMOS field of view (FOV) where the sensitivity of TB to TEC is highest. The resulting TEC global maps compare favorably with those built from the International Global navigation satellite system Service observations. TEC values obtained from A3 are next used to optimize the OTT estimation for every polarization, and proved to provide more stable values. Finally, improvements achieved in the salinity retrieved from SMOS data are reported.

Polarimetric mode of full polarization interferometric radiometer

全极化综合孔径辐射计（Full Polarization Interferometric Radiometer，FPIR）是一套高分辨率、轻量化、低功耗的X波段一维综合孔径微波辐射计.分析了FPIR的极化理论，推导出FPIR的极化可视度函数.为了获取全极化信息，FPIR系统采用两种不同的天线阵列设计方案.对于每种稀疏天线阵列，设计了最优极化切换序列.设计的最优极化序列不仅使灵敏度的损失达到最小，还使得水平极化、垂直极化和交叉极化亮温的灵敏度达到相同水平.

Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

Abstract. The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

A new space technology for ocean observation: the SMOS mission

SUMMARY: Capability for sea surface salinity observation was an important gap in ocean remote sensing in the last few decades of the 20 th century. New technological developments during the 1990s at the European Space Agency led to the proposal of SMOS (Soil Moisture and Ocean Salinity), an Earth explorer opportunity mission based on the use of a microwave interferometric radiometer, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis). SMOS, the first satellite ever addressing the observation of ocean salinity from space, was successfully launched in November 2009. The determination of salinity from the MIRAS radiometric measurements at 1.4 GHz is a complex procedure that requires high performance from the instrument and accurate modelling of several physical processes that impact on the microwave emission of the ocean’s surface. This paper introduces SMOS in the ocean remote sensing context, and summarizes the MIRAS principles of operation and the SMOS salinity retrieval approach. It describes the Spanish SMOS high-level data processing centre (CP34) and the SMOS Barcelona Expert Centre on Radiometric Calibration and Ocean Salinity (SMOSBEC), and presents a preliminary validation of global sea surface salinity maps operationally produced by CP34.

SMOS Semi-Empirical Ocean Forward Model Adjustment

A prerequisite for the successful retrieval of geophysical parameters from remote sensing measurements is the development of an accurate forward model. The European Space Agency Soil Moisture and Ocean Salinity (SMOS), carrying onboard an L-band interferometric radiometer (Microwave Interferometric Radiometer using Aperture Synthesis), was launched on November 2009. Due to the lack of L-band passive ocean measurements from space, several prelaunch forward models were developed and initially used in the SMOS ocean salinity operational processor. In this paper, an update of the prelaunch semi-empirical forward model is presented, using for the first time, real SMOS data. In particular, the ocean surface emissivity modulation at L-band due to rough sea surface is reviewed and reanalyzed. A new model definition is provided with the help of a simple neural network. The improvement is quantified in terms of retrieved salinity accuracy compared with the climatology and concerns essentially the range of wind speeds higher than 12 m·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> .

SMOS: The Challenging Sea Surface Salinity Measurement From Space

Soil Moisture and Ocean Salinity, European Space Agency, is the first satellite mission addressing the challenge of measuring sea surface salinity from space. It uses an L-band microwave interferometric radiometer with aperture synthesis (MIRAS) that generates brightness temperature images, from which both geophysical variables are computed. The retrieval of salinity requires very demanding performances of the instrument in terms of calibration and stability. This paper highlights the importance of ocean salinity for the Earth's water cycle and climate; provides a detailed description of the MIRAS instrument, its principles of operation, calibration, and image-reconstruction techniques; and presents the algorithmic approach implemented for the retrieval of salinity from MIRAS observations, as well as the expected accuracy of the obtained results.

SMOS: The Payload

The European Space Agency's Soil Moisture and Ocean Salinity satellite comprises a single payload instrument known as the Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) coupled to a PROTEUS platform. MIRAS synthesizes a large aperture from a reasonably sized 2-D array of passive microwave radiometers. By using interferometric techniques, the required coverage and spatial resolution can be achieved without the need for a large antenna. This paper describes the MIRAS instrument, its observation modes, the imaging geometry, and data products.