Abstract:Postgraduate education in military academy is a key link which shoulders important tasks of cultivating military high\|level talents, innovating the military theory and defense technology and serving the construction of combat effectiveness of the army. Therefore, in accordance with the strategic plan made by the 20th National Congress of the Communist Party, the education policy in military academy in the new era should be thoroughly implemented, the principle of cultivating morality and talents for the Party should be carried out, and fostering systems should focus attention on the following aspects, such as pushing on talent education to a new stage in accordance with the postgraduate education target attribute, playing a role in faucet in branches of learning, optimizing a top layer design, innovating a training mode, putting a comprehensive evaluation into effect, and building and strengthening a tutor contingent, etc. Simultaneously, duties incumbent on each part should be further defined, the whole resources should be taken into account and planned accordingly to form a joint educational force and cultivate many innovative military talents with both political integrity and ability of winning future war.

Abstract:Micro-motion feature extraction and recognition of ballistic targets is one of the important research directions in the field of radar targets recognition. On the basis of a brief description of the important research value of ballistic target recognition, combined with the research status at home and abroad, this paper firstly summarizes the echoes modeling methods of ballistic targets from the point scattering model, sliding scattering model, attribute scattering center model, etc., and then summarizes the micro\|motion feature extraction and imaging methods of ballistic targets from different radar observation perspectives such as monostatic radar, bistatic radar and multistatic radar. Thirdly, the classification and recognition methods of ballistic targets are summarized, which mainly based on artificial features and traditional classifiers or the deep learning. Finally, the technical difficulties and future development trends of this research directionare analyzed and forecasted.

Abstract:Inverse synthetic aperture radar(ISAR) imaging is an important means of achieving space target tracking, imaging, and identification. However, space targets' high\|speed rotating motion characteristics make the traditional ISAR imaging algorithm ineffective. Based on this, an ISAR imaging method is proposed based on Range Cell Migration Compensate(RCMC).Firstly, the echo model of the high\|speed rotating target in space is established, and then, the range cell migration compensate is made by the reference signals constructed according to the echo characteristics to realize the spatial parameter estimation of the target scattering point.Finally, the Particle Swarm Optimization(PSO) algorithm is introduced to achieve the fast parameter search. The simulation results show that the target parameters can be extracted effectively by the algorithm,realizing the high\|quality imaging in space targets. The robustness of the algorithm is verified by comparison with the traditional imaging algorithms.

Abstract:Aimed at the problems that the computational of classical sparse reconstruction algorithms is very complicated, and real\|time imaging processing capability is insufficient in radar systems subjected to the mentioned\|above faced with large\|scale radar echo data, quantum algorithms are applied to sparse signal processing of inverse synthetic aperture radar (ISAR) imaging in this paper, which brings the advantage of quantum computation in processing large\|scale data in a short time for radar sparse imaging. Firstly, based on the classical algorithm of ISAR sparse imaging, the quantization methods of classical algorithms such as matched filtering and sparse reconstruction algorithm are analyzed, and the mapping relationship between the classical algorithm and the quantum algorithm is established. Secondly, on the basis of determining the corresponding quantum algorithm and steps, a quantum circuit capable of realizing the function of the classical algorithm of sparse imaging is constructed, and an ISAR sparse imaging method based on quantum algorithms is proposed. Finally, according to the constructed quantum circuits in combination with the radar echo signal, the corresponding quantum states prepared are input into the quantum circuit to obtain the imaging results. The simulation results show that in comparison with the classical sparse imaging algorithm, the proposed sparse imaging method based on the quantum algorithms can greatly reduce the computational complexity during the data processing in radar imaging, ensuring the imaging quality.

Abstract:In view of SAR moving target imaging on the sparse scenes, a sparse imaging method is proposed based on 3\|dimensional orthogonal matching pursuit (3D\|OMP) algorithm. In this method, the imaging area is first gridded, and then the 3\|dimensional sparse dictionary matrix is constructed with the 2D motion speed of the moving target being taken as the dynamic parameter, i.e. the parametric sparse representation. In the iteration process, the support set of signals is filtered from calculating the correlation between the echo data matrix and each layer of the 3\|dimensional sparse dictionary matrix. Finally, the sparse representation coefficient on the target scene under the condition of support set is calculated by using the least square criterion. The proposed 3D\|OMP algorithm is an improvement and expansion of the classical OMP algorithm, inherits the advantages of OMP algorithm, such as low computational complexity, obvious signal sparse feature enhancement, and simultaneously has the ability to reconstruct SAR moving target images. The simulation results show that the proposed SAR moving target imaging method is valid.

Abstract:Based on plug and play (PnP) framework, a PnP 2D\|FISTA is proposed in this paper in combination with two dimensional fast iterative shrinkage thresholding algorithm (2D\|FISTA) and deep de\|noising network DnCNN for effective high\|resolution inverse synthetic aperture radar (ISAR) imaging on data with different signal\|to\|noise ratios. Firstly, models on signals and sparse observation of 2D ISAR imaging are established by this method, and iterative steps of the 2D\|FISTA are introduced. Then, being used as a de\|noiser, the trained deep de\|noising network DnCNN replaces the soft threshold shrinkage function, achievinggoodreconstruction and de\|noising performance. The experimental results show that PnP 2D\|FIST can achieveeffectively high\|resolution ISAR imaging with good reconstruction performance and noise\|robustness under different signal\|to\|noise ratio conditions.

Abstract:Being characterized by wide beam coverage and short revisit time, taking the MEO as a transmitting platform, and the missile borne Bistatic SAR as a receiver platform, the image can be made in the key areas with a wide range and high mobility. In this paper, the equivalent model of MEO space\|missile borne BiSAR is established based on the space system model, and the slant range model of the transceiver platform is described, which is equivalent to a polynomial model. The slant range error in the aperture time is analyzed to verify the validity of the model. According to the characteristics of the platform, the Doppler characteristics are re\|analyzed, and the two\|dimensional space variation characteristics of the Doppler center frequency and Doppler modulation frequency are obtained. The gradient method is used to calculate the range resolution and azimuth resolution, and analyze their changes with the imaging area. The simulation experiment shows that the resolution in the imaging area is not uniformly affected by the subduction velocity, and the oblique angle of view or the double base configuration should be changed so that the target concerned is located in the area less affected by the velocity.

Abstract:Aimed at the problems that helicopter cockpit is narrow in space, passengers are high at density of population and thermal load is heavy, and multiple passengers are thirsty for introducing a fresh cooling air of thermal comfort, an optimization design of air conditioning and ventilation system for cabin is proposed. In view of the typical helicopter cockpit layout, a three\|dimensional model of cabin and crew is built. Defining the occupant ambient temperature, temperature deviation, occupant ambient speed, PMV (predicted mean vote) and air age as thermal comfort evaluation indicators, three different layout schemes of air conditioning and ventilation systems are designed and calculated, and the optimal layout scheme is selected through the comprehensive comparative analysis of thermal comfort evaluation indicators. On the basis of the optimal layout scheme, the multi\|objective genetic algorithm is used to define the double objective function based on PMV and air age, and the simulation optimization of the location parameters of the air supply outlet of the air conditioner is carried out. Through the analysis of the result data and Pareto front, the optimal location parameters of the air supply outlet of the air conditioner are determined, and the optimal design of the cabin air conditioning and ventilation system is completed. And the accuracy and effectiveness of simulation are verified.

Abstract:In order to study the thermal comfort of human body under different air distribution in the crew cabin and find out a law of influence of intake parameters on human thermal comfort, taking the flow field results with nine intake schemes being calculated and imported into TAITherm as environmental parameters,the thermal comfort analysis is made. At the same time, two indexes of mean facial air age and energy utilization are introduced to evaluate the air distribution in the crew compartment more comprehensively. The results show that the total amount of air intake has the greatest effect on the thermal comfort and average facial air age of the three occupants, and the inlet temperature of No.1 port has the greatest effect on the energy utilization rate. In consideration of the three evaluation indexes in thermal comfort, facial average air age and energy utilization of the three occupants, it is found that the three indexes perform well and the combination of inlet air parametersis the optimal when the total air intake is 1 800 kg/h, the inlet temperatures of No. 1 and No. 2 are both at 22 ℃, and the inlet air ratio of No. 1 and No. 2 is 6∶4. 

Abstract:Taking a certain type of propeller transport aircraft powered device flight test bed as the research object, a three\|dimensional flow field model is established by CFD method with numerical calculation and meshing. The previous flight test data and engine thermal cycle model output data are used as boundary condition computational. Numerical calculations of different Mach, flight altitudes and blade angle are carried out. The engine state being characterized by the blade angle, the influence of different altitudes, speeds and blade angles on the force of the inlet front cover and additional front body force are analyzed. The calculation results show that at different altitude, the resistance of the inlet might be changed with the blade angle and Mach. When state is at 0.5 Mach and height equalsto 6 km, the blade angle increases from 40 to 50, the nacelle front force decreases by 1 700 N, and the additional front drag decreases by 3 600 N. While the flight altitude has almost no effect on the additional front body force coefficient and the front cover force coefficient. The research provides data support for determining the external resistance characteristics of the turboprop engine in the subsequent flight test.

Abstract:In order to prevent an aircraft from falling accidentally into stall/spin status in the process of flying at a high angle of attack, the modern fly\|by\|wire combat aircraft in the flight control system is usually is adopted by left boundary protection module . However, such a phenomenon is difficult to stop during use.To insure flight safety, the departure sensitivity in flying at a high angle of attack needs to be evaluated by flight testing. Traditional level\|flight speed and convergent\|turn methods are unable to fully evaluate the aircraft departure sensitivity.According to the demonstration requirement of aircraft high angle of attack departure sensitivity and spin resistance, an evaluation method based on deceleration climbing maneuver is proposed. A set of flight test maneuvers are developed by flight simulation. Moreover, the flight test procedure is built to evaluate high angle of attack departure sensitivity and spin resistance of modern aircraft with angle of attack limit and anti\|spin control law. The method and procedure are validated on a certain type of aircraft. The result show that the method and procedure could satisfy the aircraft with the demonstration requirement. 

Abstract:To address the shortcomings that the existing assignment methods in the target threat assessment process can hardly reflect the contribution of indicators and the threat level classification is too subjective, a target threat level assessment method based on random forest assignment and TOPSIS\|RSR is proposed. The method first establishes a random forest model and determines the indicator weights by calculating the correlation between the indicators and the threat values in the model. Then a threat rank assessment model based on TOPSIS\|RSR was constructed to obtain the threat ranking and threat level of the target by ranking the relative superiority and inferiority distances, and the reasonableness of the threat ranking results was tested by ANOVA analysis. Finally, the effectiveness of the proposed method is proved by simulation experiments and comparative analysis.

Abstract:Being the main radio short-range navigation system in our army, and enabling to realize the point source positioning with reliable performance, TACAN system, the only traditional land\|based radio navigation system, plays an important role in route navigation and homing guidance. Under the current realistic conditions that anti interference is poor and anti destruction ability is weak in the application of satellite navigation system, it is urgent and realistic to develop and make good use of TACAN system to improve its navigation and positioning accuracy and make it a radio navigation means with high positioning accuracy and wide coverage. Taking developing and utilizing the TACAN system as a premise to backup means that there is a quite good precision in navigating and positioning. By analyzing the ranging technology implementation ways and performance indexes of other navigation and positioning systems, the code related ranging methods and implementation technologies of TACAN system are studied, and the simulation analysis is carried out in the aspects of signal format, ranging accuracy and impact on system performance.The effect of ranging by using new coded signal is helpful to improve the tactical and technical performance of TACAN navigation system, and can also be used for the development demonstration of TACAN system equipment, and provide reference for the new generation of ranging technology.

Abstract:Although the rerouting solutions can avoid the faulty area by detouring, yet leads to the congestion of traffic around the fault with most of the existing faulttolerant routing technologies relying on the rerouting solutions. The oblivious routing algorithm reduces the routing overhead, but the faulttolerance is limited. In view of the NoC with faulty nodes or faulty links under condition of the limited network resources, a lowcost oblivious and faulttolerant routing (OFTR) strategy without virtual channels is presented to avoid the bypass loops and the bypass links in advance. If the fault from the current node and the target node are not detected, the FTOEAPA rules route data packets are adopted to achieve the diversity of routing paths. Otherwise, the priority of output port can dynamically modified according to the relative positional relationship between the source node, the current node, and the target node. By doing so, the data packets can be retransmitted through the shortest path, minimizing the number of rerouting obviously. Benefiting from the improved OEturn rule and the dynamic priority of output port rule, the OFTR algorithm can avoid network deadlock, and reduce the probability of data packets entering the fault surrounding region. The simulation results show that the OFTR algorithm increases the saturation throughput rate, and saves network overhead. Compared with other deterministic faulttolerant routing strategy, the saturation throughput of OFTR strategy increases by 8% above the average.

Abstract:Aimed at the problems that BERT model is poor in domain adaptability, and unable to cope with the problems of uneven number of training data categories and unbalanced classification difficulty, a service text classification method is proposed based on WBBI model. Firstly, the domain adaptability to the BERT model is improved by extending the BERT word list by extracting words from the domain corpus through the TF\|IDF algorithm. Secondly, the service text classification is achieved by the established BERT\|BiLSTM model. Finally, in view of the problems of unbalanced number of categories and unbalanced classification difficulty of the dataset, a zoom loss function is proposedwhich can be dynamically adjusted according to the characteristics of sample unbalance on the basis of the traditional focus loss function. In order to verify the performance of the WBBI model, a large number of comparative experiments are conducted on real datasets obtained from the Internet, and their experimental results show that the WBBI model improves the Macro\|F1 values by 4.29%, 6.59%, 5.3%, and 43% respectively incomparison with the generic text classification models TextCNN, BiLSTM\|attention, RCNN, and Transformer. Compared with the BERT\|based text classification models BERT\|CNN and BERT\|DPCNN, the WBBI model goes further at convergence rate and classifies still better results.