Abstract:Recently,paying close attention to the electronic instruments and equipment in this area is unprecedented. However, with the use of these instruments, the wave pollution of electromagnetic wave is sharpening. The demands in developing electromagnetic absorbed materials, protect not only the healthy of human body and equipment, but also a important role in the stealth of military equipment. Metal Organic Frameworks (MOFs) is a new kind of porous structure emerged in recent years. And the uniform of MOF is morphology in method, controllable in pore size, and stable in structure. Except for this, the synthesis methods of MOF is simple. The MOF-derived porous carbon not only have strong conductivity and large specific surface area, but also exposed active sites during the carbonization process, these advantages can be used in many popular application fields. In the microwave absorption, MOF-derived porous carbon materials have considerable potential. This review introduces the research status and absorbed principles monometallic of MOF-derived porous carbon, and summarizes the research progress of monometallic MOF derived porous carbon,in the microwave absorption. Based on the above-mentioned reasons, the problems of monometallic MOF-derived porous carbon absorbed materials are analyzed and the predictions for the future development are made.

Abstract:Modern information technology puts forward higher and higher requirements for chip integration and functional diversity to make the weakness of electromagnetic mode and function of traditional on-chip transmission lines (TLs) represented by microstrip line and coplanar waveguide prominent day by day. Therefore, finding the TLs with new transmission modes is an important potential path to break the technical bottleneck of chips at the physical level. Being a kind of electromagnetic metamaterials possessing the advantages of strong field binding and flexible dispersion, the spoof surface plasmon polariton (SSPP) TLs are expected to perform as the key fundamental components to realize the next generation chip technology. The research progress of on-chip SSPP TLs and their application are introduced. Firstly, the basic configuration, miniaturization design and reconfigurable design of on-chip SSPP TLs are introduced, which demonstrates the extremely high degree of freedom of on-chip SSPP TLs. Then, the applications of on-chip channel decoupling and signal modulation based on on-chip SSPP TL are introduced, which demonstrate the significant application potential of on-chip SSPP TL.

Abstract:An electronically controllable spoof surface plasmon polaritons (SSPPs) transmission line with variable transmission characteristics is designed. The dispersion curves of the SSPP unit structure in a state of on-and-off of a diode are analyzed by using an equivalent model based on a dielectric block, and the influence of different unit structure parameters on the dispersion characteristics is also examined. On the basis of these analyses, a SSPP transmission line is designed, simulated, and experimentally measured. The simulation and measurement results show that dynamic switching between passband and stopband transmission characteristics can be achieved by synchronously controlling the on-and -off state of a PIN diode. Specifically, in the on state of a diode, the passband transmission characteristics are observed with a measured 1 below -10 dB in the frequency range of 2.74 GHz to 9.47 GHz. In the off state of a diode, the stopband transmission characteristics are observed, with a measured rejection level being prior to -20 dB in the frequency range of 4.04 GHz to 5.54 GHz. The experimental results and the simulated results are identical. This work is of great significance for the dynamic control of SSPPs transmission and will greatly promote the development of active SSPP circuits and devices.

Abstract:A wideband and wide-angle beam-scanning antenna with low sidelobe levels (SLL) fed by spoof surface plasmon polaritons (SSPP) is designed. The SSPP feeding lines are adopted to excite the oval radiating patch array in the fast wave zone, whereas its low loss transmission in the slow wave zone is used to excite the spoof plasmonic antipodal Vivaldi antenna (AVA), realizing the beam scanning angle of 180° within 4~12 GHz (a relative bandwidth of 100%). And by arranging the oval radiating patches in a tapered way, the SLL during leaky-wave radiation is effectively reduced. The simulation results show that the SLL of the designed full-angle beam-scanning antenna is below -10 dB within the 4~12 GHz frequency band. Such antenna has considerable potential in application under condition of radar detection and target tracking.

Abstract:With the scanning rate of traditional spoof surface plasmon polaritons (SSPPs) leaky-wave antenna being low, a novel double layer SSPPs element is proposed, and a leaky-wave antenna with high scanning rate is realized on the basis of this. The proposed double layer SSPPs element consists of a top SSPPs element with a “H” cell and a bottom SSPPs element with a “I” element. The proposed element is characterized by independently controlling the cut-off frequency and slope of the dispersion curve, realizing the cut-off frequency and slope of dispersion curve to be controlled independently by controlling the dispersion property of the top and bottom SSPPs elements respectively. The radiation of the proposed leaky\|wave antenna is realized by sinusoidal surface impedance modulation of the “H” elements on the top layer. Due to the existence of the bottom “I” SSPPs elements, the strong dispersion property is introduced to improve the growth rate of period phase shift, thus achieving the high scanning rate. In addition, the open stopband (OSB) phenomenon of the leaky-wave antenna is almost completely suppressed by introducing short open-ended stubs in the periodic radiation structure. The prototype of the proposed leaky-wave antenna is simulated, machined and measured. The leaky-wave antenna is capable of achieving continuous wide-angle scanning from -63° to 63° at a narrow band between 8.8 GHz and 10.8 GHz. The consistency between the experimental and the simulated results proves the correctness of the proposed double-layer SSPPs element and the design theory.

Abstract:Aiming at the problem of insufficient data mining depth of the Remaining Useful Life prediction model of aero-engine at this stage, a prediction method of dual-channel model is proposed. First, a dual channel network structure is constructed: channel one uses time convolutional networks, which enables the network to have a larger receptive field and computing speed through residual structure and hole convolution; channel 2 uses convolutional long short-term memory network to extract multidimensional spatiotemporal features and capture long-term dependencies of data. Then, the multi head attention mechanism is used to reassign weights to the features of the dual channel network. Finally, the dual channel network is used for feature fusion output to achieve prediction of the remaining life of aircraft engines. Experimental validation was conducted using the turbofan engine degradation dataset and compared with other CNN-biLSTM models, multi feature attention models, multi head attention models, and CNN-GRU models mentioned in literature. The results indicate that the proposed model performs better on all three evaluation indicators, providing a new approach for predicting the remaining life of aircraft engines.

Abstract:Aimed at the problems that traditional trajectory prediction methods based on mathematical or statistical models have a certain of inherent limitations and are difficult to meet increasingly the demands of efficiency, accuracy, and real-time trajectory prediction in the modern aviation field, a novel real-time trajectory prediction method is proposed based on a CNN-LSTM model with an attention mechanism. The proposed model is that multidimensional features are extracted from trajectory data by one-dimensional convolution, reducing the number of input features. Taking the resulting multidimensional time-series data as an input of LSTM, the contextual information can be extracted by LSTM. Moreover, an attention mechanism is employed to assign weights to output from different time-series nodes within the LSTM, focusing on key trajectory information. The experimental validation shows that the proposed model in comparison with the LSTM model and the CNN-LSTM model, produces trajectory predictions to be even more close to match real trajectories. Specifically, the model in this paper achieves a 29.7% reduction in average prediction error compared to the LSTM model and a 25.4% reduction compared to the CNN-LSTM model. In summary, the proposed method significantly enhances the accuracy of trajectory prediction.

Abstract:In order to prevent excessive splashing from entering into the engine inlet, in the ARJ 21-700 aircraft, there is placed additionally between the wheels of main landing gear a water baffle, effectively improving the operation capacity of complex weather such as rain and snow. Difficulties being in existence in the flight test of water baffle strength verification-the selection of refitting position of the strain sensor and the design of test points，firstly, a splash load model is established by analyzing the splash mechanism of the aircraft wheel. Secondly, with the help of finite element analysis，the stress distribution of water baffle is determined and the strength check work is completed. According to the results of finite element analysis，the selection of refitting position of the strain sensor and the design of test points are completed. Finally, the work of water baffle strength verification is completed through flight test. The results show that the installation of water baffles can effectively change the splash pattern. The results of finite element analysis and flight test are in good agreement，which can provide useful reference for other similar complex irregular structures. The safety margin of water baffle is sufficient，and there is a large space for weight reduction，which requires further optimization of the design.

Abstract:Aimed at the problems that as the angle between the target and the jamming line of sight decreases, the anti-jamming performance of monopulse radar decreases noticeably, this paper proposes an improved anti-jamming method of monopulse radar based on distributed auxiliary antenna. Distributed auxiliary antennas are added in the radar system, the maximization of anti-interference improvement factors must be taken as a guideline, and integrated single-pulse radar beams and distributed auxiliary antenna beams are utilized for performing adaptive interference suppression in the beam domain. Finally, CFAR detection is used to verify the anti-interference performance of the proposed algorithm, in comparison with other methods. The numerical simulation results show that the proposed anti-jamming method can effectively improve the anti-jamming improvement factor and target detection probability, and has a good anti-jamming performance while the target and interference line of sight are at a small angle.

Abstract:A multi-step trajectory prediction method based on group sparse coding Kalman filtering for mobile target is proposed in this paper. Firstly, a group sparse coding is introduced, and just at that time, a simple multi-step linear prediction model is obtained by one learning, overcoming the problem that prediction accuracy is low due to the inadequate historical data with the traditional method. And then, the minimum angle regression algorithm is utilized for calculating the sparse coefficients of the above model to further improve the estimation accuracy of the model coefficients. The basic Kalman filtering algorithm is modified in combination with the group sparse coding method to ensure the precision in the prediction output. Finally, the effectiveness of the presented approach is verified by the simulation comparison among the traditional BP network, long short time memory network and the group sparse coding method.

Abstract:The extended object tracking method under condition of now available probability framework requires the statistic information of the system measurement noise, however, most of the measurement noise is unknown but bounded in real object tracking systems, and the probability-based tracking methods are difficult to estimate the position and shape of the extended object accurately. For the above-mentioned reasons, an extended object tracking algorithm is proposed based on the set membership filter with unknown but bounded noise. The proposed algorithm expresses the unknown but bounded noise by using an enclosing ellipsoidal set and by using the set membership filter to calculate state set parameters. In the process of the estimation of the object shape, the Graham scan algorithm in convex hull computational geometry theory is used to calculate the minimum boundary matrix, including the maximum error of the object shape. To obtain the updated object shape matrix, the boundary parameters of Minkowski different are calculated by using the offset hypersurface and the affine transformation. The simulation results show that the estimation accuracy of the proposed algorithm under the UBB noise is prior to the Bayesian filters based on the traditional probability framework at the state and extent of the target.

Abstract:In view of cheating behavior of the secondary user (SU) affecting the performance of non-cheating SU in the process of cognitive radio channel allocation, a channel allocation protocol named the improved top trading cycles (ITTC) is proposed according to the top trading cycle (TTC) matching theory. The ITTC allocates channels according to the preference ranking of SUs, and the behavior of changing the ranking of the true preference list is in consideration of cheating. The cheating SUs can only obtain worse allocation performance, while non-cheating SUs can obtain the same or even better allocation results than before, effectively solving the unfairness caused by cheating. For quantitatively analyzing the allocate performance indicators, a performance evaluation method of SU (PEM-SU) is designed. PEM-SU configures the PU network, as well as the arrival, distribution, and transmission of SU, and unifies the results into a form that can be quantified for performance. The experimental results compared with the secondary proposed deferred acceptance (SPDA) protocol and TTC protocol show that the ITTC is prior to SPDA and TTC in the average throughput, average latency, average queue length and average rejection rate. And also can effectively prevent strategic manipulation and protect the interests of non-cheating SUs.

Abstract:Aimed at the problems that in scene text image super-resolution, prior information is inaccurate and insufficient in utilization and text edge is incomplete in recovery, a scene text image super-resolution method guided by text semantics is proposed. This network structure is composed of a super-resolution reconstruction module and a text semantic-aware module. To further improve the expression ability of the super-resolution network, a recurrent crisscross attention mechanism is used to capture global contextual information, making the model pay more attention to the text region during training. And simultaneously, in order to generate sharp edges, a soft-edge loss and a gradient loss are proposed to constrain the reconstruction process. The performance of the proposed model is verified on the public scene text image super-resolution dataset TextZoom with eight mainstream deep network models. Compared with TSRN, the average recognition accuracy of the proposed model is promoted to 2.06%, 1.80%, and 2.89% by three different recognizers respectively, and the proposed model also has advantages in PSNR and SSIM indicators.

Abstract:Raft consensus algorithm is a reliable consistency algorithm implementation in distributed systems, but the traditional Raft algorithm is easy to make efficiency low because of malicious attacks. Aimed at the problem that the leader identity in Raft algorithm may be detected by attackers in the process of execution and then attacked, the randomness and non-interactive characteristics of verifiable random functions are utilized for improving the original Raft algorithm, and hiding the leader identity in the leader election process, avoiding the multi-round election problem in the original algorithm. This paper designs an implementation of verifiable random functions in detail, and incorporates it into the leader election process. The paper also analyzes the system security and stability of the improved scheme, compares the performance of different consensus algorithms in various requirement scenarios. The simulation experiments show that the improved algorithm hides the identity of the elected node in the leader election process, improves the system security on the premise of ensuring system stability, and also performs still more in improving the time efficiency of leader election with the increase of the number in system nodes.

Abstract:In order to evaluate the autonomous combat effectiveness of ground-attack UAV， taking actual combat as a background closely, an autonomous combat effectiveness evaluation method is proposed based on the improved ADC model. Firstly, on the basis of the traditional ADC model, the battlefield environment factors and human interference factors are introduced, and the BP neural network is optimized based on genetic algorithm to reconstruct the traditional combat capability evaluation model, and an autonomous combat effectiveness evaluation model based on ADC-BP is constructed. And then, based on the characteristics of UAV combat mission, the key capability indicators affecting the effectiveness are summarized, and an evaluation index system suitable for the combat process is constructed. Finally, taking suppression of enemy air defense mission performed by a ground-attack UAV as an example, the rationality and practicability of the ADC-BP evaluation model are verified, and this provides a new idea for the evaluation of the autonomous combat effectiveness of ground-attack UAV in the future.

Abstract:Under conditionof the dual-carbon target background, the development of new energy materials and technologies is one of the main issues. Fe-based perovskite cathode materials are potential hot materials for cathode materials of solid fuel cells at medium and low temperatures. Taking La0.5Ba0.5FeO3 as matrix materials, Ca ion is doped by replacing some Ba atoms to make the ratio of Ba and Ca double ions adjusted, and a series of cathode materials La05Ba05-xCaxFeO3 (x=0.1, 0.25, 0.4, 0.5) are synthesized by a solid state reaction method. And the phase structure, thermal expansion behavior,conductivity, electrocatalytic activity and battery electrode performance are systematically studied. The overall structure of the sample is of cubic perovskite. La0.5Ba0.5-xCaxFeO3is characterized by a good thermal compatibility with the thermal expansion coefficient of electrolyte. The maximum conductivity of La0.5Ba0.1Ca0.4FeO3 is 187.7 S/cm. The Ca doping is to greatly improve the output power density of cell with La0.5Ba0.5-xCaxFeO3as electrode to make the output power density stable relatively, and the peak power density reaches 595 mW/cm2 at 800 ℃. The doping of Ca ion can promote the performance of La0.5Ba0.5-xCaxFeO3 cathode material, and such doping material is a good candidate material for intermediate temperature solid oxide fuel cell(IT-SoFc)cathode.