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Polarimetric synthetic aperture radar (PolSAR) plays an important role in remote sensing. As a valuable application, PolSAR ship detection receives great attention and obtains fruitful achievements recently. Since ship targets’ scattering responses are highly sensitive to the radar grazing angles, robust PolSAR ship detection still faces challenges especially the very low target to clutter ratio (TCR) phenomenon at large grazing angles. How to find stable polarimetric features for robust ship detection at different grazing angles becomes the key scientific problem. This work dedicates to this issue and the main idea is to explore the potentials of polarimetric roll-invariant features which are relatively independent to radar looking directions. The main contributions are threefold. First, quantitative investigations are conducted to disclose the variation law of ship targets and sea clutters’ polarimetric scattering mechanisms in terms of different grazing angles with electromagnetic computation data and PolSAR datasets. Second, the performances of polarimetric roll-invariant features are significantly examined with the TCR and the absolute difference (AD) indexes. Five optimal polarimetric roll-invariant features with stable TCRs over the wide grazing angle range are founded, which can clearly enhance the contrast between ship targets and sea clutters at large grazing angles. Finally, robust PolSAR ship detection approaches are established with the selected polarimetric roll-invariant features. Comparison studies with Gaofen-3 and Radarsat-2 PolSAR datasets of different grazing angles are carried out. Compared with traditional polarimetric features, the experimental results demonstrate that the selected polarimetric roll-invariant features exhibit superior detection performances in terms of both detection accuracy and detection robustness.

Speckle reduction is a preprocessing for synthetic aperture radar (SAR) image interpretation and application. With the advances of convolutional neural network (CNN) models, excellent speckle filters have been continuously developed. However, supervised learning-based models suffer from a generalization deficiency due to the lack of clean SAR images. Additionally, other self-supervised learning (SSL)-based methods rely on multiple independent SAR images of the same scene to generate the filtered SAR image. In practice, these additional auxiliary datasets are not always available, which limits the application of these methods. To fulfill this gap, a novel self-supervised framework named Sublook2Sublook is proposed for single SAR images speckle filtering. The main contribution of this work lies in that a new theorem is founded which guarantee the cost function defined on the paired sublook SAR images is statistically equivalent to the supervised counterpart based on the speckled-clean SAR image pairs. Thereby, the sublook SAR images can be alternatively used for model training instead of the clean SAR images or additional auxiliary datasets. From this fashion, a complete self-supervised speckle filter is developed. First, sublook decomposition is performed in both azimuth and range directions. Then, optimal paired sublook images are selected based on a criteria of minimum L1 norm distance. Finally, the established self-supervised speckle filter can be trained with the paired sublook images. Extensive experimental studies are conducted with various SAR datasets in terms of different frequency bands and spatial resolutions from the Radarsat-2, COSMO-SkyMed, and ALOS-2 SAR satellites. Comparisons studies with four state-of-the-art despeckling methods confirm the superiority of the proposed method. The results demonstrate that the proposed Sublook2Sublook framework can better smooth speckles in homogeneous areas while well preserve image details.

This article introduces an innovative approach in synthetic aperture radar (SAR) polarimetry and proposes a novel descriptor called polarimetric autocorrelation matrix. Different from polarimetric covariance and coherency matrices, the polarimetric autocorrelation matrix can capture hidden Doppler information in the frequency domain and encode it in the phase using higher order statistical methods. This matrix facilitates the joint extraction and analysis of polarization and Doppler information from fully polarimetric SAR (PolSAR) data through a matrix analysis. This article explains that the polarimetric autocorrelation matrix can be decomposed into a Doppler-related matrix and a covariance-related matrix. The magnitudes and phases of these matrices provide insight into Doppler shifts between different polarizations and the variance of the backscattering coefficient. Our research demonstrates how the Doppler shift is influenced not only by the target’s radial velocity but also by radar polarization. Four quad-polarimetric RADARSAT-2 images are used for testing in this study, and a set of characterization features and parameters are derived from the polarimetric autocorrelation matrix. The novel descriptor, together with the new parameters, can detect man-made target and sea ice, mitigate ambiguity caused by moving targets, and indicate the motion status of ship targets and sea currents. Specifically for marine scenes, our data found Doppler differences in horizontal transmit and horizontal receive (HH) polarization and vertical transmit and vertical receive (VV) polarization induced by sea surface motion can be up to 100 Hz.

Physical parameter estimation of satellite is crucial in space situation awareness as it reflects valuable information. Polarimetric inverse synthetic aperture radar (Pol-ISAR) is a powerful sensor for space surveillance, providing rich information for satellite physical parameter estimation. Parabolic antennas, which are widely loaded in remote sensing and communication satellites, have received great attention recently. Dedicated to the space situation awareness issue using Pol-ISAR, a physical parameter joint estimation method of satellite parabolic antenna with key frame Pol-ISAR images is developed in this work. The core idea is to utilize the mapping relationship between parabolic antenna in 3-D space and its projection ellipse in 2-D ISAR image. Under special observation geometry, the closed-form expressions of parabolic antenna physical parameters are deduced for the first time, providing an efficient way for parameter estimation. Moreover, the abundant information within Pol-ISAR images is mined and utilized. Various polarimetric features are adopted for ellipse extraction and the subsequent physical parameter estimation. Compared with single-polarization channel data, the superiorities of polarimetric feature are validated using electromagnetic simulation data.

Attitude estimation of space targets can reveal crucial details about payload orientation, movement intentions, and observation area, all of which are vital in space situational awareness. Till now, inverse synthetic aperture radar (ISAR) has become a mainstream sensor for space target observation, providing rich information for space target attitude estimation. Based on projection matrix and linear structure extracted from ISAR images, a space target attitude estimation method is proposed in this work. The main contribution falls on two parts. On the one hand, linear structure is derived based on the peak accumulation values of original ISAR images rather than binary images. On the other hand, the space target attitude information is effectively estimated based on the projection matrix theory and linear structure extraction results. Experimental studies with measured and simulated data demonstrate the effectiveness of the proposed method.

A challenging issue in the field of marine remote sensing is the application of polarimetric synthetic aperture radar (PolSAR) to small ship detection in complicated environments. Several outstanding polarimetric detectors (such as the optimal polarimetric detector, polarimetric whitening filter (PWF), and polarimetric notch filter (PNF)) have been effectively implemented in practical applications. A linear combination model based on quadratic optimization is summarized to establish a general framework for polarimetric detectors, transitioning the PolSAR ship target detection from a model-driven approach to a hybrid (model/data)-driven approach. However, the dimension of the covariance matrix may be high, and the computation cost will be large. The higher dimension of the covariance matrix requires a bigger data demand. As a result, when the sample size is small, the model performance will degrade. In this article, to decrease the computational complexity and improve the robustness, we propose a novel method called the simultaneous diagonalization transform (SDT). The proposed method enables an almost simplest representation of information from the covariance matrix providing a rapid detection algorithm. The simulation experiments demonstrate that polarimetric detectors based on SDT consistently outperform those based on other methods in terms of accuracy, efficiency, and sample size requirements across various complex backgrounds. Furthermore, the effectiveness, robust, and fastness of the polarimetric detector based on SDT is validated using real data collected by RadarSAT-2 (RS-2), GaoFen-3 (GF-3), and Sentinel-1A.

Polarimetric inverse synthetic aperture radar (ISAR) can operate all-day and all-weather, making it crucial for space surveillance. The compact polarimetric (CP) mode balances hardware complexity and polarimetric information, which is commonly equipped with ISAR systems. Given the constraints of limited physical conditions, exploring ISAR image super-resolution is worthwhile. Currently, deep learning models have been employed for enhancing ISAR image super-resolution. However, the super-resolution performance is limited by local interpolation and the occurrence of artifacts. To address these limitations, this work presents a non-local scene awareness network (NLSAN), which incorporates a non-local interpolation approach to capture global textures. Furthermore, a scene awareness scheme is established by integrating semantic and super-resolution information, concerning the varying levels of artifacts in different regions. The training process can be regulated by a designed penalty function to mitigate potentially generated artifacts. A dataset of CP ISAR images of satellite targets is constructed for comparison analysis. The proposed NLSAN method yields more elaborate super-resolution results with fewer artifacts. Quantitative evaluations are also carried out using global and local indexes, such as the peak-signal-to-noise ratio (PSNR), the image entropy, and the 3 dB width of strong scatters. Compared with the typical state-of-the-art methods, the proposed approach achieves superior super-resolution performance, with an overall performance improvement of at least 9.2% and enhanced generalization capabilities.

AbstractThis study investigates the failure mechanism and strengthening effect of a shield tunnel lining structure reinforced via steel plates with corbels. A detailed three-dimensional (3D) numerical model is established for the staggered-joint segmental lining structure of an actual shield tunnel in the Kunming metro-system, which is then validated via a full-scale simulation experiment of the shield tunnel segmental lining structure. Then, the actual loading conditions of the staggered-joint shield tunnel segmental lining structure in the Kunming metro-system are simulated, and the mechanical responses of the segmental lining are analysed in terms of the variation in its diameter, opening amount of the joints and stress of the bolts. The ultimate load-bearing capacity of the lining structure reinforced using steel plates with corbels is improved to 610 kN, which is 41.9% higher than the unreinforced structure with an ultimate load-bearing capacity of 430 kN. Moreover, the strengthening effect of the reinforcement using steel plates with corbels is discussed considering actual field monitoring data and other reinforcement methods. It is concluded that the results of this paper can provide an effective reference for similar reinforcement schemes of shield tunnels. The defined classification criteria can be adopted to determine the deformation stage of reinforced shield tunnels.

A copper-catalyzed [3 + 2] annulation of O-acyl oximes with 4-sulfonamidophenols is developed. The advantage of this method lies in the concurrent double activation of two substrates to form nucleophilic enamines and electrophilic quinone monoimines. The substituent on the α-carbon of O-acyl oxime determines two different reaction pathways, thereby leading to the selective generation of 5-sulfonamidoindoles and 2-amido-5-sulfonamidobenzofuran-3(2H)-ones.

The influences on the performance of wet flue gas desulfurization system in mercury removing after adding mercury removal additive were studied. As a consequence, the mercury removal efficiency can be improved by this kind of additive, that the efficiency of elemental mercury and total mercury is raised along with the amount of additive is increased. And so can the desulfuration efficiency. The oxidation of calcium sulfite in desulfurization is promoted by the mercury removal additive, increase the reduce speed of calcium sulfite concentration.

Fractionation of heterotrophic bacteria (HB), ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) in a full-scale Unitank wastewater treatment plant (WWTP) were analyzed based on oxygen utilization rate (OUR) test, and the effect of simultaneous chemical phosphorus removal on microbial activity was investigated by adding aluminum sulfate and ferric chloride to activated sludge. Proportions of HB, AOB and NOB in the full-scale Unitank WWTP were 67.0%, 21.0% and 12.0%, respectively. 12.5mg Al3+ showed significant inhibition of microbial activity, and inhibitory ratios on HB, AOB and NOB were19.6%, 11.5% and 29.0%, respectively. Nevertheless, the inhibitory ratios of 13.8mg/L Fe3+ on HB, AOB and NOB were 4.1%, 5.5% and 4.8%, respectively. Al salt demonstrated much higher inhibitory effects on microbial activities than ferric salt, and the inhibition of Al salt on NOB is dominant in the nitrification process.

The article presents an analysis of the problems, situations, experiences and innovation development of university high level sports teams. It describes how the innovative development has depended on the unity between the university and the clubs, or that between the university and the sports bureau or provincial professional sports teams.