Interferometric Radiometer Research Articles

Molecular Dynamics Simulation of Methane Adsorption and Diffusion

To study the adsorption and diffusion mechanism of low-rank coal at the microscopic level, samples of Fukang low-rank coal were collected, and the elemental composition, carbon type distribution and functional group type of the Fukang low-rank coal structure were determined by elemental analysis (Ea), Fourier-transform interferometric radiometer (FTIR), X-ray photoelectron spectroscopy (XPS) and 13C nuclear magnetic resonance (13C NMR) experiments to construct a 2D molecular structure of the coal and a 3D macromolecular structure model. The adsorption and diffusion characteristics of methane were researched by giant regular Monte Carlo (GCMC) and molecular dynamics (MD) simulation methods. The results showed that the excess adsorption amount of methane increased and then decreased with the increase in pressure. The diffusion of methane showed two stages with increasing pressure: a sharp decrease in the diffusion coefficient from 0.5 to 5.0 MPa and a slow decrease in the diffusion coefficient from 5.0 to 15.0 MPa. The lower the pressure, the larger the effective radius of the CH4 and C atoms, and the higher the temperature, the more pronounced the diffusion and the larger the effective radius.

A Principal Component Analysis Perspective for RFI Mitigation in Synthetic Aperture Interferometric Radiometer

A Principal Component Analysis Perspective for RFI Mitigation in Synthetic Aperture Interferometric Radiometer

A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

Development and application of lead smelting slag eco-cementitious material: Synergistic excitation regulation and heavy metal solidification

In order to realise the resource reuse and safety of lead smelting slag (LSS) that contains several harmful heavy metals, LSS eco-cementitious materials (LSSEM) were prepared in this study using calcium and magnesium sources to excite high-volume LSS (78.125%). The results show that the synergistic effect of dual excitation sources can significantly increase the compressive strength of LSSEM from 13 MPa to 34.44 MPa. Performance enhancement mechanisms were investigated using X-Ray Diffraction (XRD), Fourier Transform Interferometric Radiometer (FTIR), Thermal Gravimetric Analysis (TG), Scanning Electron Microscope (SEM), and Mercury Intrusion Porosimetry (MIP). Introduction of calcium and magnesium sources facilitated dissolution of the active components in the LSS to achieve greater excitation. Leaching experiments showed that LSSEM could significantly solidify heavy metals based on the synergistic action of the dual excitation sources. The solidification ratio for each heavy metal exceeded 70%, and the leaching of heavy metals conformed to drinking water quality standards. The slump of pavement concrete prepared with LSSEM was 130 mm, and its 28-d flexural tensile strength and compressive strength were 6 MPa and 49 MPa, respectively, meeting the requirements for pavement concrete design with light traffic load. A conceptual model of the synergistic stimulatory effect of calcium and magnesium sources on LSS excitation was developed. This study promotes solid-waste recycling and provides complementary cementitious materials with lower energy consumption and CO2 emissions for the construction industry.

A Novel Distance Estimation Method for Near-Field Synthetic Aperture Interferometric Radiometer

The visibility samples generated by the synthetic aperture interferometric radiometer (SAIR) under near-field observation conditions contain information about the distance from the target to the instrument. This requires a precise understanding of the target–instrument distance to guarantee imaging quality in near-field SAIR applications. In this paper, we introduce a novel distance estimate approach for near-field SAIR systems, which achieves satisfactory imaging performance in the absence of prior information on target–instrument distance. First, we reformulate the signal model of near-field SAIR from the fractional Fourier transform (FRFT) perspective. This formulation ties the distance that is variable to the visibility function in a straightforward manner, offering an efficient solution for image reconstruction in near-field SAIR. Subsequently, we present an iterative strategy for target–instrument distance estimation based on simulated annealing (SA). In each iteration, the modified average gradient (MAG) of images reconstructed within the FRFT framework is evaluated, and based on the Metropolis criterion, the estimated target–instrument distance is optimally updated iteratively. Finally, the validity and effectiveness of the proposed distance estimation method for near-field SAIR imaging systems are demonstrated through numerical simulation and real experiments.

Molecular Dynamics Simulation of Methane Adsorption and Diffusion: A Case Study of Low-Rank Coal in Fukang Area, Southern Junggar Basin

Adsorption and diffusion are the key factors affecting coalbed methane (CBM) accumulation, resource assessment and production prediction. To study the adsorption and diffusion mechanism of Fukang low-rank coal at the microscopic level, samples of Fukang low-rank coal were collected, and the elemental composition, carbon type distribution and functional group type of the Fukang low-rank coal structure were determined by elemental analysis (Ea), Fourier-transform interferometric radiometer (FTIR), X-ray photoelectron spectroscopy (XPS) and 13C nuclear magnetic resonance (13C NMR) experiments to construct a 2D molecular structure of the coal and a 3D macromolecular structure model. The adsorption and diffusion characteristics of methane were researched by giant regular Monte Carlo (GCMC) and molecular dynamics (MD) simulation methods. The results showed that the excess adsorption amount of methane increased and then decreased with the increase in pressure. The diffusion of methane showed two stages with increasing pressure: a sharp decrease in the diffusion coefficient from 0.5 to 5.0 MPa and a slow decrease in the diffusion coefficient from 5.0 to 15.0 MPa. The lower the pressure, the larger the effective radius of the CH4 and C atoms, and the higher the temperature, the more pronounced the diffusion and the larger the effective radius.

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.

Target Imaging Using Compressed Sampling in Synthetic Aperture Interferometric Radiometer

The target imaging application is significant to various sensing systems, such as radiometers, radars, and infrared. However, high system complexity impedes the application of interferometric radiometers to target imaging tasks to some extent. Specifically for an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -element interferometric radiometer with aperture synthesis technique, complex correlators are of the order of O( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), giving rise to the great difficulty of system hardware implementation. In this paper, we propose a new compressed interferometric radiometer (CIR) concept for target imaging applications, which exploits the sparsity property of targets in the spatial domain. The CIR target imaging framework mainly adopts the compressive measurement method to acquire partial visibility function samples in the spatial-frequency domain via a proper sparse sampling pattern. Then, these partially observed visibility samples are inverted to image the target contrast information by sparse recovery methods. For the above image recovery process, we propose two novel algorithms named local regional information-based reweighted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> 1-norm minimization (LRRL1) and local regional convolution-based reweighted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> 1-norm minimization (LRCRL1). The experiments using simulated and real data demonstrate the validity and effectiveness of the proposed CIR target imaging framework, showing superiority in both imaging performance and system complexity compared with conventional algorithms used in interferometric radiometers.

A Combined RFI Localization Algorithm of BT Image and Subspace Decomposition for Synthetic Aperture Interferometric Radiometer

Radio frequency interferences (RFIs) in the L-band heavily contaminate remote sensing data and bring many challenges to the product quality of synthesis aperture interferometric radiometers. Detecting and localizing RFIs is the urgent need for switching off these RFIs and conducting mitigation algorithms. The localization algorithm based on the brightness temperature (BT) image is limited by the resolution to separate closely spaced RFIs and achieve high localization accuracy in some cases. To achieve super-resolution, the MUSIC method using subspace decomposition technique is suggested. Nevertheless, when the BT image SNR is low, the power of RFI is insufficient to overwhelm the background scene, and the performance of the MUSIC algorithm is unsatisfactory. In this paper, a further improvement is proposed by combining BT image and subspace decomposition. In the BT image domain, background scene cancellation and RFI target enhancement are carried out for enhancing the SNR. In the frequency domain, the MUSIC algorithm is applied utilizing subspace-decomposition to achieve super-resolution localization. Experiments and simulations based on SMOS data validate that the method presented in this paper performs better than both the classical MUSIC algorithm and BT-based localization algorithm in low SNR cases.

Distance Adaptive Imaging Algorithm for Synthetic Aperture Interferometric Radiometer in Near-Field

Distance Adaptive Imaging Algorithm for Synthetic Aperture Interferometric Radiometer in Near-Field

Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer

Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer

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.

A Fast Near-Field Image Reconstruction Algorithm via Band-Limited Filtering for Synthetic Aperture Interferometric Radiometer

A Fast Near-Field Image Reconstruction Algorithm via Band-Limited Filtering for Synthetic Aperture Interferometric Radiometer

A Coastal RFI Mitigation Method for Synthetic Aperture Interferometric Radiometer

This letter pays attention to the mitigation of the Radio Frequency Interference (RFI) sources located at coastal regions for Synthetic Aperture Interferometric Radiometer (SAIR). To remove an RFI at the visibility level, it will be necessary to estimate the Brightness Temperature (BT) of the point source, which is currently done by computing the median of the surrounded pixels to get the background BT, and subtracting it from the original contaminated BT. However, this strategy is based on the assumption that the background BT distribution around the RFI is flat, and this is not reasonable for those RFIs from coastal cities, and could result in estimation deviation. A robust RFI mitigation method is proposed without introducing complex computing. Instead of focusing only on the local area, the basic idea of our method is to step into the wide area, and minimize the overall fluctuation of the pixels affected by the RFI in the BT image. The method tests based on SMOS visibility samples validate the correctness of the developed method.

RFI Detection and Mitigation for Advanced Correlators in Interferometric Radiometers

This work presents the first RFI detection and mitigation algorithm for the interferometric radiometers that will be implemented in its correlator unit. The algorithm operates in the time and frequency domains, applying polarimetric and statistical tests in both domains, and exhibiting a tunable and arbitrary low probability of false alarm. It is scalable to a configurable number of receivers, and it is optimized in terms of quantization bits and the implementation of the cross-correlations in the time or frequency domains for hardware resource saving. New features of this algorithm are the computation of the Stokes parameters per frequency bin in the Short-Time Fourier Transform and a new parameter called Polarimetric Kurtosis. If RFI is detected in one domain or in both, it is removed using the calculated blanking masks. The optimum algorithm parameters are computed, such as length of the FFTs, the threshold selection for a given probability of false alarm, and the selection of the blanking masks. Last, an important result refers to the application of Parseval’s theorem for the computation of the cross-correlations in the frequency domain, instead of in the time domain, which is more efficient and leads to smaller errors even when using moderate quantization levels. The algorithm has been developed in the framework of the ESA’s technology preparation for a potential L-band radiometer mission beyond SMOS. However, it is also applicable to (polarimetric) real aperture radiometers, and its performance would improve if more than one bit is used in the signal quantization.

A Near-Field Imaging Algorithm Based on Angular Spectrum Theory for Synthetic Aperture Interferometric Radiometer

For the near-field synthetic aperture interferometric radiometer (SAIR), the Fourier transform relationship between the visibility function and the near-field brightness temperature (BT) distribution is not valid. It is a challenging task for near-field SAIR imaging to realize very close-range accurate imaging with a large field of view (FOV). This article presents a new SAIR near-field imaging algorithm based on the angular spectrum theory to realize the passive millimeter-wave (PMMW) imaging, called synthetic-angular-spectrum imaging (SASI) algorithm. This SASI algorithm mainly addresses data samples of a 4-D visibility function acquired from planar arrays. First, we invert 4-D visibility samples into the angular spectrum domain via the Fourier transformation. The obtained angular spectrum data cannot be directly used to estimate the near-field BT distribution. Second, a dedicated phase factor compensation is adopted for handling this problem. The dimension-reducing accumulation is employed to generate the synthetic angular spectrum (SAS) of near-field BT distribution. Finally, we reconstruct the BT image by using the generated SAS data. Simulation and experiment results show that the presented SASI algorithm has the superiority on image reconstruction quality, especially for the off-axis regions, compared with the existing near-field SAIR imaging methods.

Synthesis and Application of a Low Dye Absorption Waterborne Polyurethane for Microfiber Synthetic Leather

As increasing attention is being paid to harmful residual dye pollution in the dyeing effluent from the microfiber synthetic leather industry, there is an urgent need to explore innovative ways to alleviate such pollution. Here, a low-polarity waterborne polyurethane (WPU) was synthesized using hydroxyl-terminated polybutadiene (HTPB) and polypropylene glycol (N220) as soft segments to react with –NCO on isophorone diisocyanate (IPDI). The structure and properties of modified waterborne polyurethane were characterized by Fourier Transform Interferometric Radiometer (FTIR), and emulsion characterization was performed, including particle size and zeta potential analysis, tensile test, thermal properties test, and contact angle test. The SEM and alkali reduction rate results showed that increasing the HTPB content decreases the alkali reduction rate by blocking the penetration of corrosive ions by the double bond cross-link structure, but higher HTPB addition (&gt;40%) leads to an enhancement in phase separation, which contributes to an increase in the alkali reduction rate. The results of the UV spectrum analysis showed that when the amount of HTPB added was 50%, the coloration rate reached 81.27% compared with 13.18%, which was 68.09% higher than that of the unmodified microfiber leather. The binding of the dry and wet rubbing color of the modified microfiber leather with the addition of 50% HTPB reached grades of 4–5 and 3–4, respectively, which meets most application requirements without subsequent washing.

Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer

Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer

Performance Simulation of the Payload IMR and MICAP Onboard the Chinese Ocean Salinity Satellite

The Chinese Ocean Salinity Satellite is dedicated to global sea surface salinity (SSS) mapping with two payloads onboard, which are the interferometric microwave radiometer (IMR) and the microwave imager combined active and passive (MICAP), both using the interferometric aperture synthesis radiometry. One of the payloads is an L-band interferometric radiometer system with a Y-shaped antenna array. The other one, MICAP, is a 1-D passive/active combined system, where the L-, C-, and K-band interferometric radiometers’ antenna arrays are arranged in a line, and the active device is an L-band scatterometer. Based on the payload configurations, a series of simulations is applied to analyze the payloads performance, including the brightness temperature (TB) characteristic, the SSS accuracy, and the effects of Sun and land contamination. The TB simulation results show that the IMR possesses a finer spatial resolution compared to the MICAP L-band radiometer, whereas the latter achieves a better TB radiometric resolution. With the assistance of the C- and K-band radiometers and the L-band scatterometer, the combined retrieval accuracy improves compared with the SSS retrieved using only L-band TB and auxiliary parameters. The best accuracy of SSS is achieved when considering all the available measurements from two payloads together in a combined retrieval. Finally, the results related to Sun and land contamination that endanger the interferometric radiometer measurements are presented and discussed. The performance simulation in this article has been used as a reference for the design phase of two payloads and will be updated with the development of payload manufacture.

Adaptive L p Reconstruction Method for Synthetic Aperture Interferometric Radiometer

The brightness temperature reconstruction of synthetic aperture interferometric radiometers (SAIRs) is an underdetermined and ill-posed inverse problem. The classical Hilbert-space regularization methods have often the disadvantages of the over-smoothness effects and the oscillations. In this paper, an adaptive Lp reconstruction method in Lebesgue spaces is introduced to obtain the accurate brightness temperature map in SAIRs. The proposed approach can adaptively adjust the exponent p between 1.2 and 2 according to the region of the map to be re-constructed. The experimental results show that the Lp reconstruction method can effectively reduce over-smoothness and Gibbs oscillations, and better improve the accuracy of the inverse results, compared to the traditional minimum-norm and band-limited regularization methods.