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In this study, aiming at fulfilling the requirement of polarization acquisition and utilization, a method for active deception jamming recognition based on the time-varying polarization-conversion metasurface is investigated. First, an anisotropic phase-modulated metasurface supporting 3-bit phase quantization in the 9.6～10.1 GHz frequency band is designed. By optimizing the periodical phase coding, the polarization state can be converted on demand. And then, loading the polarization-conversion metasurface on a single polarization radar antenna so that the polarization states of the antenna can change along a specific trajectory. By extracting the difference in the polarization domain between target and active deception jamming, the active deception jamming could be distinguished from the radar echo. The simulation results show that under the constraints of three different polarization trajectories, the active deception jamming and targets exhibit a significant clustering effect, and the identification effect is stable. Compared with jamming identification methods that rely on dual-polarization or full-polarization radar systems, the proposed method has both low cost and high efficiency, which has great application potential in radar anti-jamming.

Inverse Synthetic Aperture Radar (ISAR) images of spacecraft are composed of discrete scatterers that exhibit weak texture, high dynamics, and discontinuity. These characteristics result in sparse point clouds obtained using traditional algorithms for the Three-Dimensional (3D) reconstruction of spacecraft ISAR images. Furthermore, using point clouds to comprehensively describe the complete shape of targets is difficult, which consequently hampers the accurate extraction of the structural and pose parameters of the target. To address this problem, considering that space targets usually have specific modular structures, this paper proposes a method for abstracting parametric structural primitives from space target ISAR images to represent their 3D structures. First, the energy accumulation algorithm is used to obtain the sparse point cloud of the target from ISAR images. Subsequently, the point cloud is fitted using parameterized primitives. Finally, primitives are projected onto the ISAR imaging plane and optimized by maximizing their similarity with the target image to obtain the optimal 3D representation of the target primitives. Compared with the traditional point cloud 3D reconstruction, this method can provide a more complete description of the three-dimensional structure of the target. Meanwhile, primitive parameters obtained using this method represent the attitude and structure of the target and can directly support subsequent tasks such as target recognition and analysis. Simulation experiments demonstrate that this method can effectively achieve the 3D abstraction of space targets based on ISAR sequential images.

After Wenchuan earthquake, many large debris flow have occur in Banzi Gully. Especially in 2019, the "8·20" debris flow caused serious damage to the roads，bridges and villages in the gully mouth, mail river was seriously squeeaed to the other side and there is a big risk of blocking the river in the future. Based on the field investigation and comprehensive analysis of the basic characteristics and formation conditions of the debris flow, the characteristics of river blockage are analyzed, the parameters of river blockage under different debris flow frequency are calculated, and the possible impact of dam-breaking flood under each frequency on Miansi Town is predicted. The results show that debris flow with frequencies of 2%, 5% and 10% are less likely to cause river blockage of Min River, and if there was a river blocking event , the town of Miansi would not be exposed to dam-breaking flood. The debris flow with a frequency of 1% are likely to cause river blockage. The debris flow material with a volume of 57.38×104 m3 can reach the Min River to form a dam with a height of about 51.61 m. Under the action of the main river flood (1890.0 m3/s), the dam will be broken, and the peak flow rate of the flood was 5935.49 m3/s, which dropped to 2312.25 m3/s while arrive at Miansi Town. Since the flood depth (4.00 m) is higher than the height of the protective embankment (3.5 m), the flood is likely to damage the houses near the protective embankment of Miansi Town.This paper provided a reference for the analysis of the characteristics of large-scale debris flow blockage in the future, as well as the possible impact of the collapse flood on downstream towns.

ObjectivesThis paper aims to study the coupling interaction between a truss box floating raft and submarine hull, and proposes a design approach for enhancing the vibration isolation effect of the truss box floating raft-hull coupling system. MethodsFirst, modal analyses of the aforementioned coupling system and individual floating raft and hull structures are carried out respectively, and comparisons are made of the modal shapes between the floating raft of the coupling system and individual floating raft structure, as well as between the hull structure of the coupling system and individual hull structure. The effects of the thickness of the floating raft panel and isolator stiffness on the isolation of the coupling system in the full-frequency range are then investigated. ResultsThe floating raft of the coupling system shows little difference in natural frequency or modal shape compared with the individual floating raft, and the vibration isolation effects are also the same. In addition, the increase in the thickness of the panel and the weakening of the stiffness of the lower vibration isolator will improve the vibration isolation capability of the coupling system. ConclusionsThe results of this study indicate that the mutual influence between the floating raft and hull is small, and can be considered a weak coupling relationship.

The traditional tracking and traceability system based on ARM9 and ZigBee and the tracking and traceability system based on STM32 have poor anti-interference ability, which leads to the low consistency between the cold chain food information transmitted and the actual information, resulting in poor tracking and traceability effect. In order to solve this problem, on the basis of designing SSH framework to process logistics information, genetic algorithm was combined to extract tracking and traceability features, and the cold chain logistics tracking scheme was designed. The experimental results show that in recognition experiments of 90 times, the effective recognition times of the system are available, the minimum effective times can reach 83 times, and the average success rate of traceability can reach 94.55%. The results show that the system can effectively track and trace the cold chain logistics information.

The communication system between the islands has the problems of high cost and the transmitted signal may require relay amplification. In order to solve this issue, a novel Free Space Optical (FSO) communication system using Manchester encoded and decoded signals is designed. It can support 10 Gbit/s optical signal transmission over 100 km submarine cable (using G. 654 standard single-mode fiber) cascaded with 1 km FSO wireless link. We evaluate the performance by measuring the time-domain waveform, optical spectrum, eye diagrams and Bit Error Rate (BER) in simulation with Manchester coded signals, under sunny, rainy and foggy day. The measured results show that the receiver sensitivity can reach -18.92 dBm at the back-to-back system. Under the 100 km submarine cable and 1 km FSO wireless link, the receiver sensitivity can reach -17.72, -16.66 and -11.16 dBm in the sunny, rainy and foggy day, respectively. The simulation results prove that the FSO communication system using Manchester code may have potential application in the field of islands information transmission in the future.

To improve the cross-range resolution of three-dimensional (3-D) images obtained along the direction of movement by Multiple-Input Mmultiple-Output (MIMO) radar, a novel MIMO-ISAR 3-D imaging method that combines multi-snapshot images is proposed. This method integrates multiple single-snapshot 3-D images acquired by a planar antenna array during a specific period of observation and extracts the peak slice along the linear fitting direction of the scatterers to construct a new 3-D image. The simulation results demonstrated that the proposed method significantly improves the cross-range resolution of the imaging results along the direction of movement compared with other methods based on single-snapshot 3-D images. Additionally, compared with the classical MIMO-ISAR method based on rearrangement and interpolation, this method is suitable for both fast-moving and slow-moving targets. Moreover, the imaging results are well focused and the side lobes along the direction of movement are effectively suppressed.

The low hardness and poor wear resistance of titanium alloy severely restrict its service life under friction conditions. Wear-resistant and self-lubricating coatings prepared on titanium alloy surface by laser cladding technology can greatly improve its wear resistance. In this paper, firstly, the influences of laser cladding technology(laser power, scanning velocity, spot diameter, specific energy, post-heat treatment, high frequency vibration, etc.) on the wear resistance of the coatings were reviewed. And then, the characteristics of different types of hard phases, matrix phases and self-lubricating phases as well as their influences on the wear resistance of the coatings were discussed. Finally, the wear-resistant and self-lubricating coatings prepared on the surface of titanium alloy by laser cladding were summarized and prospected.

In order to improve the performance of unsupervised hash learning and achieve robust hashing image retrieval,this paper proposes a novel robust hash learning method based on dual-teacher self-supervised distillation.Specifically,the proposed method contains two stages:a self-supervised dual-teacher learning stage and a robust hash learning stage.In the first stage,a modified cluster algorithm is designed to effectively improve the accuracy of hard pseudo labels.Then,we fine-tune the teacher networks by hard pseudo labels to get the initial soft pseudo labels.In the second stage,we filter the initial soft pseudo labels by our soft pseudo label denoising method,which combines a hybrid denoising strategy and a dual-teacher denoising strategy.Then,we train the student network with the denoised soft pseudo labels by knowledge distillation,so that robust hash codes for label-free images are obtained.Extensive experiments on CIFAR-10,FLICKR25K and EuroSAT datasets show that the proposed robust hash learning method outperforms the state-of-the-art methods.In detail,the MAP of our method is 18.6% higher than that of the TBH method on CIFAR-10,2.4% higher than that of the DistillHash method on FLICKR25K,and 18.5% higher than that of the ETE-GAN method on EuroSAT.

Ensemble learning is one of the most popular methods for nonlinear systems. However, when the traditional ensemble models of TSK fuzzy classifiers are directly applied to imbalanced data, their learning performances will be deteriorated with poor generalization ability. In order to tackle with this issue, a TSK-fuzzy-classifier-based ensemble method for imbalanced data is proposed in this paper. The basic idea is to first pre-process the imbalanced dataset by the SMOTE method to achieve the corresponding balanced dataset, and then take the AdaBoost strategy to ensemble several TSK fuzzy classifiers so that satisfactory performance is got. During the training of the proposed ensemble model, randomly sampled data will be dynamically and iteratively weighted to feed as the inputs into each TSK fuzzy model, and then each trained TSK fuzzy classifier is weighted to form the final outputs of the ensemble model, so that each model can be fully trained, and then the generalization ability of the whole ensemble TSK fuzzy model is improved. Therefore, an ensemble TSK fuzzy model corresponding to imbalanced data is proposed, and the model is used to experiment on multiple datasets. The mean square error (MSE) and accuracy are used to evaluate the model, then the number of models and rules are changed to explore their effect on model performance, and images are used to show their changes. The experimental results demonstrate the effectiveness of the proposed ensemble model.

The content of polyethylene glycol 6000 in Hydroxyethylidene diphosphonic acid (HEDP) copper plating solution was determined and studied by iodine precipitation-spectrophotometry.Results showed that the copper ions in HEDP copper plating solution reacted with iodine and interfered with the measurement results.After shielding copper ions with oxalic acid，the content of polyethylene glycol 6000 in HEDP copper plating solution could be accurately determined.The standard recovery rate was 98.08%～99.12%，and the recovery rate of spiking was 98.24%～98.80%.Moreover，the error of measurement method could meet the requirement of production control.