Abstract:Based on the research progress on microwave absorption performance of monometallic MOF-derived porous carbon, this article continues to study the current status and absorption principles of multimetal MOF derived porous carbon materials, and their advantages compared to the single monometallic MOFs derived-porous carbon. The research progress of bimagnetic metal MOF derived-porous carbon,single magnetic metal MOF derived-porous carbon, and trimetal MOF-derived porous carbon were discussed in this paper, respectively.In view of the above progress, we analyzed the problems of multi-metal MOF-derived porous carbon absorbed materials and made the predictions for the future development.

Abstract:In order to realize the absorption of radar waves in low-frequency band, the thickness of Magnetic Absorbers (MAs) or the weight is on the increase under normal conditions, and actual applied potentialities are restricted. For the above-mentioned reasons, this paper proposes a method based on Plasma Meta-material (PM) to regulate the internal magnetic field of conventional MAs. The short metal wires are utilized for enhancing the magnetic field distribution in the entire local space between it and the metal backboard, and the overall structure will have a stronger absorption after adding conventional MAs. The simulated results show that the proposed Plasma Meta-material Absorber (PMA) can achieve efficient absorption in the frequency band of 0.84~2.08 GHz at vertical incidence, and the bandwidth of -10 dB can still remain 0.7~2.95 GHz even at an incidence angle of 60°. This design method may find the potential applications in the fields of electromagnetic compatibility, wireless communication, and so on.

Abstract:As a national strategic-level vehicle, a helicopter certainly plays a key role in the nuclear, biological and chemical threat with its ability being capable of rapidly entering and exiting battlefields. To ensure the safety of personnel in cabin, it is necessary to study the NBC protection system of helicopters. In this paper, a helicopter nuclear, biological, and chemical (NBC) protection system is designed in turn from the top-level architecture design of the system based on system integration means. Detailed configuration design is conducted for each sub-system, including air source pressurization sub-system based on a small high speed electric pressurizer, filtration and ventilation sub-system based on the principle of variable pressure adsorption and real-time regeneration on board, temperature control sub-system based on a heat pump-type evaporative refrigeration cycle driven by the use of skidding oil waste heat and parallel drive of double evaporators, and pressure regulation sub-system with integrated cockpit over-pressurization protection and pressurization requirements. Based on the system configuration, a simulation model is established and the dynamic performance of the system is simulated and verified. The simulation results show that under various extreme conditions, both the cabin pressure and the temperature meet the needs of design. While a helicopter enters into the area of NBC threat, the filtration and ventilation subsystem can effectively adsorb toxic substances, and the adsorbent bed is regenerated in real time by on-board, prolonging the operation time in the NBC threat area. The research provides a new idea for the design of helicopter NBC protection system.

Abstract:In view of the structure characteristic of the force of the load and the transmission force on tristrut connected landing gears, holistic load calibration but regressing loads modal respectively test method are adopted for the first time, the three struts landing gears are installed and loaded as one, and the effect problem among the struts loads are resolved successfully. With loads and structure analysis, strain gauges and loads cases are designed for the struts with I -shaped section and large obliquity, and loads cases include single strut cases, as well as combination loads cases of two or three struts. General reference coefficient of multi-strut is put forward to analyze the effect among the struts loads. The result indicates that the loads are transferred forwards, the latter one affects the proximate front one, but the front one doesn't affect the latter one. In terms of this result, the policy of regressing loads modal is put forward which is regressing loads modal respectively and calculating struts loads one by one, then deducting the influence between struts according to the general reference coefficient. The test method is impactful and the loads modals meet the needs of precision.

Abstract:Aimed at the problems that the degradation parameters monitored by aviation engine sensors are difficult to be extracted, is subject to noise interference, and accuracy is insufficient in predicting engine remaining useful Life (RUL), a new remaining useful life prediction model is proposed by utilizing the maximal information coefficient (MIC), bayesian optimization (BO) algorithm, and categorical boosting(CatBoost) algorithm. Firstly, to effectively address the issue of inadequate feature extraction, the collected historical monitoring features of sensors are subjected to maximal information coefficient correlation calculation to extract key degradation features from the significant impact on the engine's operational lifespan.Secondly, to address the gradient bias and prediction offset issues in remaining useful life prediction,the categorical boosting algorithm method based on bayesian optimization is employed to predict the remaining useful life of aero engines. Finally, experiments are conducted on the commercial modular aero-propulsion system simulation (C-MAPSS) dataset provided by national aeronautics and space administration (NASA). The results show that the proposed prediction method has a good performance, and is valid.

Abstract:The analysis of aircraft dynamic radar cross section (RCS) is capable of providing an important theoretical support for aircraft stealth design and test evaluation. The shortcomings of current dynamic RCS modeling and simulation are analyzed. Aimed at the problem that the existing dynamic RCS calculation method is simply applied to finite angle domain, the definition of radar azimuth in the aircraft system is modified, and the scope of application of existing methods is expanded. In the existing methods, a oneto-one mapping relationship between the radar line-of-sight angle and the aircraft RCS value cannot be established,and a new dynamic RCS calculation method is proposed. This method is to use the dynamic RCS value of the aircraft characterized by the Euler rotation angle in the aircraft body coordinate system and in the radar irradiation coordinate system, and has higher accuracy in the comparison with the traditional method. The simulation verifies that when an aircraft is in a maneuvering state, the results of the new dynamic RCS calculation method are significantly different from those of the existing methods, and such method effectively improves the accuracy of the dynamic RCS calculation.

Abstract:Aimed at the problem that temperature affects the load measurement accuracy of composite structure by the strain method, a load measurement method is proposed in consideration of the effect of temperature on composite structure. In this paper, taking shear force measurement of carbon fiber composite in horizontal tail box at a certain type of aircraft as an example, tests are to be made. Firstly, the load calibration tests under different temperature environments are designed and completed. Secondly, the multiple linear regression method is used to establish a load measurement model at room temperature, and the load model is checked under different temperature conditions. Finally, the load model at room temperature is modified and verified in consideration of the effect of temperature. The results show that the method in this paper is feasible and the result is accurate

Abstract:Aimed at the problems that the deployment of ground-based anti-aircraft fire interception equipment is slow at speed and the deployment scheme does not conform to the actual environment of the battlefield,a deployment method of ground-based air defense intercept systems by using simplified artificial bee colony algorithm is proposed. In this method, in the process of formulating the deployment scheme of ground-based anti-aircraft fire interception equipment, the artificial bee colony algorithm is divided into an initialization stage and an optimization stage. In perspective of expert knowledge assistance, the initialization stage is intended to utilize the expert knowledge for optimizing the deployable location in combination with random initialization, and the optimization stage is intended to utilize the simplified neighborhood optimization for optimizing the scheme generated in the initialization stage. The resulting deployment schemeis verified in both stages, and the output is directly saved if the scheme reaches the given penetration probability index, greatly improving the convergence speed, and the resulted deployment scheme is realistic.The simulation results show that the proposed method has obvious advantages over the traditional bee colony algorithm at convergence speed, and can conform well to the battlefield environment.

Abstract:The construction of war case event map is a key measure in improving the decision-making capability of edge operations. Based on the in-depth study of edge combat, auxiliary decision-making and knowledge graph, a war case event map is presented. Firstly, the logical structure of war event graph is described, the elements and associations of war events are sorted out, and the knowledge representation model of war event graph is constructed, and then, through the case event data source selection, event extraction and event relationship identification, the practice of case event map construction is conducted to verify the feasibility of the model. On the basis of this, the application mode and methods of the war case event map in intelligence analysis, situational awareness and scheme formulation are explored. The war case event map is a great help to realizing the structured organization and effective management of combat knowledge, and making full use of the computing power and technology of the central node to improve the edge combat command ability

Abstract:With the development and integration of information technology and aerospace technology equipment, the collaborative operation of early warning aircraft in aerospace is the trend of the times, and it is necessary to significantly improve the overall combat effectiveness. Taking the collaborative operation of air and space force as a core, and the early warning aircraft as an object, a typical model of cooperative attack operations is performed by the early warning aircraft under conditions of battlefield environments in the air and the space. The background of remote strikes carried out by early warning aircraft in cooperative combat with the information supported by the electronic reconnaissance satellite is constructed, and an ant colony optimization algorithm is introduced to analyze and simulate the mission plan and operational effectiveness of air space cooperative combat. This paper put forward some countermeasures and suggestions from the aspects of combat concepe,strength construction,combat trainning,and personnel training.

Abstract:Taking an improvement on the efficiency of aerial combat training evaluation as a target, and staring at the key nodes of influence on trend of combat outcomes, this paper proposes a method for determining aerial combat key nodes based on win rate prediction. Firstly, the long short-term memory networks are utilized for designing and training a win rate prediction model for real-time assessment of aerial combat situations. Secondly, the OTSU's method is utilized for determining the threshold for key nodes,and the time steps with absolute win rate difference between adjacent steps of being greater than the threshold are identified as key nodes. The experiments show that the win rates are accurate in prediction by the designed win rate prediction model, the adopted key node threshold selection method is reasonable, and the overall proposed method is feasible and has a good generality.

Abstract:Aimed at the problem that air target group intent is often difficult to be identified rapidly under condition of imbalanced and difficult classification, an intent recognition method is proposed based on moving-window estimation of the temporal convolution self-attention network model. First, the proposed model is intended to preprocess the feature data by the moving-window estimation method. Second, the flow information of multi-dimensional time series feature data is quickly extracted by the temporal convolution network (TCN). Finally, the self-attention mechanism is used to capture the key features from each feature datum and optimize the weights. The simulation results show that this method improves the training efficiency and classification accuracy for the intent recognition of hard-sample in imbalanced samples.

Abstract:In order to improve the accuracy of the radar registration method in the process of large error primary radar measurement, taking the track data of the broadcast automatic correlation monitoring system as the true value, the characteristics of the primary radar error distribution are analyzed, and a realtime radar registration method is proposed based on the improved track tracking filter. This method is intended to improve the bias function in the variable structure interactive multi-model algorithm (EMAIMM) based on the expected increase model by adopting the iterative nearest point method (RANSACICP) of random sampling consistency in point cloud registration method, effectively reducing the influence of random errors in the registration process, obtaining the optimal bias parameters, and improving the accuracy of large error primary radar registration. The results show that the average absolute error of pitch Angle and azimuth Angle can be reduced to 0.04° and 0.07° respectively, and this provides a new method for radar system error registration.

Abstract:Data serving as a basic strategic resource is playing an important underpinning role in joint combat system. The proper management and efficient use of data are an important driving force in promoting the overall transformation of combat capability and the deep transformation of combat style. In order to realize the information interconnection between different combat systems, a multi-source heterogeneous network data fusion method is proposed based on the federated learning. In view of the security and heterogeneity of multi-source data, the conditional generation adversarial network is utilized for extracting local knowledge and global distribution, and integrating data information. In combination with the local teacher model-global model architecture, the local model knowledge is transferred by distillation of knowledge without data, the heterogeneous network is fused, and the global model is refined to realize safe and highquality information interaction between different systems, providing technical support for the construction of intelligent command information system. The experimental results show that the proposed method is feasible on structural data sets and image data sets, and the overall accuracy can be more than 80%.

Abstract:For the low altitude target elevation direction finding scenario of bistatic multiple input multiple output (MIMO) radar, due to multipath effects, the transmitting and receiving steering vectors lose orthogonality with the noise subspace due to coupling, resulting in the unavailability of subspace class algorithms mainly based on multiple signal classification (MUSIC) in this scenario, However, subspace algorithms based on spatial smoothing preprocessing suffer from low accuracy in angle estimation due to array aperture loss. To solve the above problems, this paper establishes a bistatic meter wave MIMO radar single target and incoherent multi target mirror reflection signal model. Based on the mathematical transformation and analysis of the signal model, a steering vector matrix that is still orthogonal to the noise subspace is discovered, then, a new guidance vector matrix combined with generalized MUSIC and maximum likelihood algorithm was used to propose a joint estimation method for the elevation direction of departure and arrival of low altitude targets in a bistatic meter wave MIMO radar. Finally, simulation experiments verified the effectiveness of the proposed method and the superiority of the elevation direction finding performance.

Abstract:Aimed at the problems that while paying attention to the text-based person re-identification models often relying on global and local feature in alignment, very often the inter--modal and intra-modal correlations are in negative, a cross-modal pedestrian re-identification method is proposed based on relationship mining. The method includes a dual-stream network backbone, negative similarity mining module,and relationship encoder module. Firstly,the global and the local feature are in alignment through the dual-stream network backbone. Secondly the granularity of feature discrimination is enhanced by using the negative similarity mining module, and the similar incorrect results are filtered out. Finally, the relationship encoder module is utilized for respectively learning the latent relationship information in both the image and text, achieving relationship-level feature alignment. The experimental results on the CUHKPEDES dataset and the ICFG-PEDES dataset show that this method achieves recognition accuracy higher.

Abstract:Aimed at the problem that individual identification of communication radiation sources has a certain lack of label data under conditions of non-cooperative communication, a method of individual identification of communication emitter is proposed based on deep clustering. The powerful feature extraction and data reconstruction capabilities of the auto-encoder network are utilized for carrying out the representation learning of the original I/Q data, extracting the fingerprint features of individual recognition, and jointly optimizing the representation learning process and the feature clustering process, so as to achieve a higher fit between the representation learning and the feature clustering, and complete still greater individual identification of the communication emitter without labels. The experimental results show that the recognition accuracy is more than 85% when the SNR is above 0 dB. And the proposed method is valid and stable.

Abstract:Based on the defining vector of binary linear code, new concept of generalized anti-code of a given code is introduced into this paper, and the defining vector of a generalized anti-code is described by the given code. The parameters of a generalized anti-code are utilized for determining corresponding binary optimal code. It is proved that 11 classes of binary optimal codes are not LCD codes. And such method breaks through the limitations of the current methods, and provides a new theory and a new method for study of LCD parameters determination and structure.