Abstract:The absorbing coating covered in the surface of equipment is apt to have the damage of abrasion, bulging, aging after used for a long period of time. In this paper, the three damage modes and its influence on absorbing performance are investigated by the reflectivity and phase measurement and microwave imaging. The above three kinds of damage samples of radar absorbing coating and infraredradar absorbing coating are made, reflectivity and phase are measured with arch method, and microwave images are built by the radar scattering imaging system for stealthy target. With the comparison of the experimental results and qualitative analysis, it is found that the all of the damage on coating make the absorbing performance deteriorate, its corresponding absorbing band become narrow, and a shift due to the variation in structure and composition of absorbing materials. However, the wear damage mode has the most serious impact on the two kinds of microwave absorbing coatings, resulting in a sharp decline in the absorption capacity

Abstract:Taking the double swept flying wing as a base outline in consideration of stealth performance, a wingtip is reshaped. The numerical simulation method is utilized for studying the influence of wingtip shape on the longitudinal aerodynamic characteristics and longitudinal stability of double swept flying wing. The result shows that for the double swept flying wing, the sheared wingtip can provide forward thrust, reduce the drag, increase the maximum lifttodrag ratio, and enhance the longitudinal static stability. Different shapes of sheared wingtip have different effects. Under condition of flying at a cruising speed, compared with the basic wingtip, the best sheared wingtip can reduce the drag by 7.9%, increase the maximum lifttodrag ratio by 11.9% and increase the static stability margin by 10.8%. The results of the article can provide certain references for the selection of the wingtip shape of the double swept flying wing.

Abstract:The aeroengine is a main contribution to the backward electromagnetic scattering of the aircraft, and the radar cross section(RCS) reduction measures adopted enable to effectively improve the aircraft stealth performance. The spherical convergent flap nozzle (SCFN)can meet the comprehensive needs of new generation fighters for maneuverability and stealth. The iterative physical optics method is used to calculate the backward RCS of the spherical convergence vector nozzle under different angles of beveling and tooth modification. The results show that the beveling modification has a better RCS reduction ability at the pitch plane. When the beveling is at an angle of 30°, the reduction ability is better than that of the other beveling angle. The tooth modification has RCS reductionability at the both plane. When the tooth angle is at an angle of 100°, the reduction ability is better than that of the other tooth angle. The shape modification of aero engines requires comprehensive consideration in the aircraft design stage.

Abstract:With the increasing military application of unmanned combat aircraft (UCAV), unmanned combat will become the main combat mode in the future air battlefield. In closerange air combat, the environment is complex and the combat situation changes rapidly. The method based on game theory cannot meet the realtime requirements due to the large amount of data iteration, and the datadriven method has the problems of long training time and low execution efficiency. To solve this problem, a UCAV maneuver decision method based on deep reinforcement learning algorithm is proposed in this paper. Firstly, the flight drive module is constructed on the basis of UCAV threedegreeoffreedom model to form the state transition updating mechanism. Then, on the basis of PPO algorithm, ornsteinuhlenbeck (OU) random noise was added to improve UCAV's ability to explore unknown state space, and LSTM was combined to enhance UCAV's ability to learn sequence sample data, so as to improve the training efficiency and effect of the algorithm. Finally, the effectiveness and superiority of the proposed method are verified by designing three groups of closerange air combat simulation experiments and comparing the performance with PPO algorithm.

Abstract:Aimed at the problems that sensing nodes are uneven in distribution and low in construction efficiency in the construction of electromagnetic spectrum map, a new electromagnetic spectrum map construction algorithm is proposed based on the Kriging algorithm. Firstly, the Kriging algorithm is used to build electromagnetic spectrum map from perceptual data. Secondly, the Kmeans clustering algorithm is introduced to realize the multigranularity division of the perception region, and the whole region is divided into multiple local regions at different levels. Meanwhile, the Kriging algorithm is used to interpolate and estimate the electric field intensity of the local region, and the multiple electromagnetic spectrum maps with different granularity are formed. Finally, according to the distribution of sensing nodes, the weight of local region uniformity under different granularity is calculated based on the Voronoi diagram, and the electromagnetic spectrum map under different granularity is weighted, generating the electromagnetic spectrum map. The simulation results show that the proposed algorithm can reduce the error of electromagnetic spectrum map construction by 2%～5%, and the construction efficiency is much higher than that of the original algorithm when the noise intensity is greater than 8 dBW, and the algorithm is characterized by high construction accuracy and strong fault tolerance.

Abstract:In the communication process of traditional cooperative relay, the relay node itself amplifies the interference signal of the relay node while processing the signal. In addition, eavesdropping nodes often exist in real communication scenarios to steal important information. Intelligent reflecting surface (IRS) is characterized by passive reflection, enabling to adjust the phase of the signal, and reducing the generation of interference signal during signal processing. In view of increasing interference signal and secure transmission of relay nodes, a cooperative secure transmission technology based on IRS is proposed. In consideration of malicious eavesdropping nodes existence in communication scenarios under condition of high correlation between eavesdropping links and legitimate links, the IRS enables to reflect the signals sent by base stations to legitimate users, improving the quality of secure communication of the system. In order to solve the nonconvexity of the secret rate expression, alternate optimization and Riemannian conjugate gradient descent algorithms are used to alternate optimization of beamforming vector and reflection phase. Finally, the simulation results verify that under the 3 GHz high frequency carrier, based on the IRS cooperative communication technology is superior to the traditional relay cooperative communication method in terms of data transmission, energy efficiency and security.

Abstract:A dynamic spectrum division process based on graph theory is proposed in the scenario of multiauthorized user satellite cognitive communication between satellite and ground networks. First of all, the graph theory model is introduced. Secondly, this paper analyzes the cognitive authorized users under the condition of satellite communication scenarios. According to the cognitive users perceive, the paper makes use of the graph theory model with the authorized users perception of the matrix, and uses the throughput of the cognitive users and the authorized user of spectrum idle state parameters such as communication by iteration to get the final spectrum access matrix and completed many authorized users under the condition of spectrum. The simulation results show that the algorithm can divide cognitive users into the spectrum of authorized users with the highest revenue within the range of cognitive users perception ability.

Abstract:The orbital angular momentum carried by the vortex light enables the capacity of the communication system to effectively expand and meet the increasing communication needs of people. However, when the vortex light is transmitted at the atmosphere, the wavefront will be distorted due to the influence of atmospheric turbulence, resulting in an increase of the bit error rate at the receiving end. In order to ensure the reliability of communication, the correction for the distorted wavefront is needed. Adaptive optics technology with wavefront sensors can produce a phase of conjugation with distorted wavefront in counteracting the effects of atmospheric turbulence. The principle is to utilize the wavefront sensor for detecting the wavefront information and reconstructing the wavefront distortion, and finally correcting it by the wavefront corrector. The effect of wavefront distortion correction mainly depends on the accuracy of the reconstructed wavefront. The existing model method, area method and other methods have low accuracy of reconstructed wavefront. In the paper, a wavefront reconstruction based on wavelet fractal interpolation algorithm is proposed. Compared with the traditional MVE algorithm, the root mean square error of the reconstructed wavefront is reduced from 3.249 2 to 0.634 6, and the reconstructed wavefront error is greatly reduced. At the same time, the accuracy of reconstructed wavefront is also improved.

Abstract:For lack of gradient tensor large field error in magnetic localization system, a firstorder magnetic gradient tensor localization method is proposed based on immune cloning algorithm. First, the crossform sensor model is utilized for deriving the firstorder magnetic gradient tensor localization principle. Then, an error gradient matrix calculating method is proposed by using the magnetic field decay law and the immune cloning algorithm is optimized. To verify the effectiveness of the new algorithm, three different routes are used in Matlab for onestep metric tensor localization and optimization algorithm localization calculation and to verify the new localization algorithm through actual localization experiments .It is found that the firstorder magnetic gradient tensor localization method based on the immune cloning algorithm can effectively improve the accuracy of the magnetic positioning system.

Abstract:Aimed at the problems that the traditional RRT algorithm pays high price in searching unnecessary areas and in planning path under conditions of complex environment, a fast expanding random tree algorithm is proposed, i.e. TNCGRRT* (twoway simultaneous noncollision goal based RRT*). In this algorithm, the bidirectional search strategy in BRRT* and the heuristic search fusion in BIT* are taken as a basic algorithm of this paper, and the batch size of neural network is introduced to determine the number of nodes sampled at one time, affecting the sampling speed. And then, the expansion of forward and reverse trees is carried out simultaneously to speed up the path search, and the expansion direction is defined by improving the extended vertex queue in the target bias strategy and updating the sampling area, and the growth range of random trees is reduced. Finally, the cubic Bspline curve is 〖JP2〗utilized for making the generated path smooth. The experimental results show that compared with the BRRT* algorithm and the BIT* algorithm, the TNCGRRT* algorithm can shorten the path generation time by 4.5%, the number of pruning increases by 80%, and the path cost (i.e. path length) is shortened by 9%, and is valid.

Abstract:In order to improve the feature expression ability of the target tracking algorithm based on Siamese network and obtain better tracking performance, a lightweight Siamese network target tracking algorithm based on secondorder pooling feature fusion is proposed. First, the Siamese network architecture is used to obtain the deep features of the target; then, the secondorder pooling network and the lightweight channel attention are added in parallel at the end of the Siamese network architecture to obtain the secondorder pooling features and channel attention features of the target, respectively. Finally, the depth feature of the target, the secondorder pooling feature and the channel attention feature are fused, and the fused feature is used for crosscorrelation operation, and the obtained response graph can distinguish the target and the background well, and improve the discriminative ability of the model, and improve the accuracy of target positioning, thereby improving target tracking performance. The proposed algorithm only uses the Got10k dataset for endtoend training and is validated on the OTB100 and VOT2018 datasets. The experimental results show that the proposed algorithm achieves a significant improvement in tracking performance compared with the benchmark algorithm SiamFC: on the OTB100 dataset, the accuracy and success rate are increased by 7.5% and 5.2%, respectively; on the VOT2018 dataset, the expected average overlap rate increases by 4.3%.

Abstract:Aimed at the problems that being affected by multipleaperture influence such as small array aperture, low angle measurement accuracy and poor performance, etc., large angle measurement error still remains in spite of the fact that the existing low elevation estimation algorithms mostly are mostly used by the uniform linear array (ULA) signal model for echo reception and processing, and then use the superresolution algorithm for low elevation estimation, are approximately feasible, and the performance is not good, a real valued low elevation estimation method based on physical array of CPA is proposed. Firstly, the signal model is established by using CPA, and the echo signal covariance matrix is calculated according to the position of physical array element. Then, after real value processing, the accurate low elevation is obtained by using maximum likelihood (ML) estimation or generalized multiple signal classification (MUSIC) algorithm. Finally, the target height is obtained by using geometric relationship. The simulation experiments compare the low elevation estimation performance of ULA and CPA virtual array, and prove the accuracy and superiority of the proposed low elevation estimation method based on physical array of CPA.

Abstract:Aimed at the problems that large range migration and severe rangeazimuth cross coupling remain in returning echo under condition of the highlysquinted synthetic aperture radar imaging (SAR) mode, the conventional polar format algorithm (CPFA) is modified and a method for highlysquinted SAR is proposed. According to the actual echo data storage form, the algorithm establishes a slanted data model of the highlysquinted SAR, and designs a twodimensional interpolating function of the slant range plane through the expansion of the twodimensional Taylor series in the range and azimuth directions, effectively improving the depthoffocus. Moreover, the modified polar format algorithm (MPFA) is more suitable for the undulating terrain because the projection of real data onto ground plane performed in CPFA is avoided. The simulation and real data experiments show that the proposed approach is valid.

Abstract:Taking joint air operations as the background, an air cluster threat assessment method based on the change of battlefield situation is proposed. First, a threat assessment index system for air cluster is established, and a quantified threat index model based on hierarchical aggregation is constructed based on the similar principles of discrete sources and weapons and equipment; the subjective and objective weights are obtained by the analytic hierarchy process and the entropy weight method, and the constant weight is obtained by the game combination. the variable weight theory is introduced to determine the variable weight, so that the index weight can reflect the characteristics and changes of the battlefield situation; then, the traditional multiattribute decisionmaking method does not consider the psychological factors of the decision maker and the gray correlation analysis and the TOPSIS method evaluation results are inconsistent. A grey TOPSIS threat assessment model based on regret theory is proposed, and the final threat assessment result is obtained by calculating the comprehensive closeness. Finally, the effectiveness of the method is proved by simulation experiments.

Abstract:In order to study the effect of low modulus synthetic fiber on basic creep of concrete, three creep tests of low modulus synthetic fiber concrete with different dosage are carried out, and the test results are compared with the calculation results of relevant prediction models. The results show that though the addition of low modulus synthetic fiber has little effect on the compressive strength and elastic modulus of concrete, the basic creep of concrete increases. Compared with the concrete samples without fiber, the creep degree of 0.8 kg/m3, 1.2 kg/m3 and 1.6 kg/m3 concrete samples increase by 7.9%, 10.1% and 100% respectively. The creep coefficient increases by 15.3%, 17.2% and 1.9%, and the total compressive strain per unit stress increases by 1.1%, 2.3% and 8.9% respectively. The measured result of concrete creep degree has the highest agreement with ACI209R model, followed by CEBFIP model. However, neither of them can be directly used to predict basic creep of lowmodulus fiber reinforced concrete, and the relevant parameters of the formula need to rely on shortterm test for regression. However, the GL2000 model has a large error and is not suitable for the prediction of creep of low modulus synthetic fiber concrete.

Abstract:Aimed at the problems that nonlinear systems are confronted with uncertain dynamics, unknown external disturbances and input constrains, an asymptotic tracking controller considering input saturation is proposed. Firstly, the uncertain dynamics and external disturbances in the system are integrated into the bounded "total disturbance term". Then, the control law and the adaptive law are designed to compensate the disturbance term to make the tracking error asymptotically converge to zero rather than just a bounded compact set. Compared with the traditional control method of nonlinear systems considering uncertain dynamics and external disturbance, the proposed controller is simpler in structure and the proposed method is good in precision. In addition, by designing an auxiliary error compensation system, the controller can cope with the input saturation situation well, and the compensation signal can converge to zero asymptotically after the saturation condition is removed. Finally, the proposed method is valid.