Abstract:In order to counter the tendency of collaborative tracking and rounding up control of multiple unmanned aerial vehicle (multiUAV) to track intrusive aircraft, a strategy of multiUAV cooperate is used to capture an escaped target. This strategy introduces the escaperounding phenomenon of natural biota when the catching becomes a prey. The roundup process consists of two stages. At the first stage, the control method based on dynamic feedback linearization is applied to track the escaped target accurately. At the second stage, the Lyapunov vector field (LVF) method is utilized for ensuring the UAV to avoid dangerous areas such as enemy air defense forces and radar detection in counter flight. The simulation results show that the designed strategy in the scenario of multiUAV rounding up and preventing target escape is valid and feasible.

Abstract:The hunting of dynamic targets by multiUAV is an important problem in UAV swarm operations. In this paper, aiming at the dynamic target oriented swarm hunting problem, by analyzing the shortcomings of the hunting mechanism based on MADDPG algorithm, and learning from the attention mechanism used by Google machine translation team, we introduce the attention mechanism into the hunting process, design the cooperative hunting strategy based on the attention mechanism, and construct the corresponding hunting algorithm. Improve MADDPG based on AC framework. First of all, the attention module is added to critical network to process the information of all UAVs according to different attention weights; then, the attention module is added to actor network to promote other UAVs to carry out cooperative hunting. The simulation results show that AttMADDPG algorithm can improve the training stability by 8.9% and reduce the task completion time by 19.12% compared with MADDPG algorithm. After learning, the UAV can cooperate to make the swarm emerge more intelligent behavior.

Abstract:In close air combat, it is very important to get a piece of reliable air combat situation information in time for decisionmaking guidance. Aimed at the problems that there are drastic changes in the situation of close air combat and multidimensional coupling of evaluation parameters, a multielement air combat situation segmentation clustering method based on LKshapeHACA is proposed. Taking the hierarchical time series cluster analysis as a framework, the number of clusters is determined by using the Laplace centrality method, and the cluster analysis on multivariate time series is made by using Kshape, solving the problem of situation information extraction under multidimensional parameters. The test is performed by using the 12 sets of close air combat data, and the 14 clustering algorithms are compared. The results show that LKshapeHACA is more consistent with the actual air combat situation in the accuracy of cluster center determination and situation segmentation.

Abstract:In order to study the detection and identification technology of foreign object impact on fan blade at noninterference blade tip vibration measurement, a fan blade test platform for detection and identification of foreign object impact is designed and built. Lots of experiments are carried out under different working conditions such as projectile mass、launching speed and fan speed. The criterion of foreign object impact identification is preliminarily given before the identification results are verified at high speed camera. The difference of the recognition accuracy under different projectile mass and rotating speed conditions, and qualitative rule between impact factors and blade tip vibration is analyzed. The result shows that the detection and identification system could accurately determine the impact event with the number of impact blade. The identification accuracy of the system reaches 100% under conditions of fan speed within the range of 1800~4000 r/min, and the mass of the projectile is greater than 2.90 g. The above mentioned provides important test data and basis for establishing intelligent detection and identification methods for foreign object impact.

Abstract:The damage tolerance analysis of wing external store mounting pylon structure is an important content to ensure the safety of structure and achieve the expected target mission. At present, nobody cares to make inquires about the damage tolerance analysis and research on the UAV wing external store mounting pylon. Taking a highaspectratio UAV wing combined probe pylon as an example, the damage tolerance analysis of the wing external store mounting pylon is made. According to the structural design features of wing combined probe pylon, a finite element analysis model of pylon is established, and the fatigue analysis dangerous points are determined by stress analysis of fatigue load conditions. And the random spectrum compilation method is adopted to obtain the damage tolerance load spectrum of the analyzed part. Based on the fracture mechanics, the RungeKutta method is used to estimate the crack propagation behavior, obtaining the crack growth characteristics and curve of the analyzed part. The analysis results show that the crack propagation life of the analyzed part of the pylon is 11,615,250 flight cycles, meeting the expected design requirements of residual strength value. And the inspection interval can be determined according to the crack propagation life.

Abstract:Aimed at the problems that the noise components are complex and the fault features in fiber optic gyro output signals are hard to extract, a fault diagnosis method based on improved sparrow search algorithm and support vector machine (SVM) is proposed. Firstly, the normal and the fault signals of fiber optic gyro are decomposed by threelayer wavelet packet to extract feature vectors. Secondly, by introducing the improved Logistic chaotic map and adaptive t distribution strategy, and adding the boundary exploration and alarm cancellation mechanism, the ISSA is proposed and applied to the parameter optimization of SVM. Finally, a SVM model is established for fault identification and diagnosis of fiber optic gyro. The results show that the method proposed in this paper can be effectively used in fiber optic gyro fault diagnosis, and simultaneously effectively improve the accuracy of fiber optic gyro fault diagnosis compared with the sparrow search algorithm, the gray wolf optimization, the particle swarm optimization, the genetic algorithm and the Beetle Antennae Search.

Abstract:In order to meet the lowpower IoT node application in the 5G environment, this paper proposes a new type of harmonic suppression load structure in rectifier circuit, which introduces a continuous multiorder microstrip harmonic suppression structure behind the diode to achieve higher conversion efficiency and lower output ripple. The compact circuit has low design cost and simple structure. When the input power is14.8 dBm, the conversion efficiency can reach 72.5%. Finally, the F4B substrate is selected for experimental verification. The results show that when the load is 750Ω, the highest conversion efficiency of the circuit can still reach 61.2%, which is significantly improved compared to other structures.

Abstract:Aimed at the problems that the parameter setting of traditional DBSCAN algorithm relies on the unreliability of manual experience, and the heterogeneous data clustering effect is poor, A CMDBSCAN model is proposed based on Cloud model. Firstly, according to the characteristics of the distance curve angle mutation, the adaptive neighborhood radius is obtained. And cluster density threshold is set according to the distribution density of radar signal, realizing DBSCAN algorithm run adaptively. And then, in combination with the theory of multidimensional cloud model, the validity of DBSCAN algorithm sorting results is evaluated, and the decision results are used to further optimize parameter setting. The experiment is carried out according to the radar signal received during the complex countermeasure process. The result shows that the algorithm can realize the adaptive sorting of nonuniform radar signals and effectively deal with the “batch” problem in multimode radar signal sorting.

Abstract:Aimed at the problem that computation measure is comparatively heavy by the joint estimation algorithm of information source azimuth and polarization state of conformal array antenna, a forward recursion method of multistage wiener filter for cylindrical conformal array antenna is derived, and an efficient joint estimation algorithm of information source azimuth and polarization parameters based on fast subspace estimation is presented. Taking the signal of a desired signal as known conditions, this algorithm realizes the signal subspace and noise subspace quick estimate through multistage wiener filter forward recursive, avoiding the covariance matrix estimation and eigenvalue decomposition, greatly reducing the computational cost for joint estimation algorithm, and reducing amount of calculation from the original O(N3+N2L) to O(N2L). The computer Monte Carlo simulation experiment shows that the algorithm can guarantee the estimation accuracy and simultaneously reduce the complexity of the algorithm. When the SNR is greater than 10 dB, the algorithm has approximately the same estimation accuracy compared with the existing algorithm. And the algorithm is valid.

Abstract:Aimed at the problem that the Underlay mode power control algorithm based on energy efficiency fails to accurately reflect the interference performance between the secondary users and the primary users resulting in system capacity degradation, the interference efficiency is defined as the ratio of the total transmission rate of the cognitive satellite user to the interference received by the terrestrial base station, taking into consideration of the limited energy of the secondary users and the difference between the satellite link and the terrestrial link, an interference efficiencybased uplink power allocation model for satelliteground cognitive networks is established. On the basis of the abovementioned, an interference efficiencybased power allocation algorithm is proposed. By introducing the interference threshold constraint and the signaltonoise ratio constraint, the optimal power is solved by using the nonlinear fractional programming theory and the Lagrange duality method. The simulation results show that the algorithm in this paper can effectively reduce the interference to the primary user and improve the interference efficiency of the system under conditions of premise in satisfaction of the communication quality of secondary user.

Abstract:The 5Gsatellite integrated network based on the SDN architecture will be one of the most promising solutions of global coverage and broadband communications. In this integrated network, the key of effective deployment of controllers and gateways lies in improving network reliability and reducing time delay. Although the deployment of the controller and the gateway can be solved independently, the tightly coupled nature of the deployment of the controller and the gateway makes the joint deployment more realistic. This paper analyzes and models the joint deployment of SDN controllers and satellite gateways in 5Gsatellite integrated networks, proposes a joint deployment strategy of controllers and gateways based on maximizing network reliability, and designs a mixed algorithm based on simulated annealing and particle swarm Hybrid. The simulation results show that compared with the existing algorithms such as enumeration algorithm and dual simulated annealing algorithm (SASA), the algorithm proposed in this paper has lower time complexity, and further reduces the average control delay and improves the robustness of the network.

Abstract:Micro-Doppler (m-D) in ballistic targets is characterized by applying an important means to warhead recognition. However, when the micromotion of the ballistic targets is accompanied by macromotion, the timefrequency representation is no longer a sinusoidal modulation curve. Aimed at the problem that the microDoppler feature extraction method based on the sinusoidal hypothesis of timefrequency representation may become ineffective, an estimation algorithm based on circular autocorrelation function (CACF) in combination with the circular average amplitude difference function (CAMDF) is proposed to obtain the circular coefficient matrix of timefrequency representation and average circular coefficients of the matrix, estimating the mD period of ballistic targets. The algorithm does not need to assume with the target macromotion having been accurately compensated and the shortcomings of traditional mD period estimation methods having been overcome effectively. The feasibility of the algorithm is demonstrated by theoretical derivation, and the effectiveness and antinoise of the algorithm is verified by simulation experiments.

Abstract:Format string vulnerability is a common and harmful software vulnerability. The misjudgment of the exploitability posed by software vulnerability is as much about some of the existing format string vulnerability automatic exploit generation system as the parameter storage location is outside the stack. In view of this problem, an automatic exploit generation method of format string vulnerabilities is designed based on symbolic execution. First, the current format string function vulnerabilities are detected according to the parameter symbol information, and then the exploit constraints with parameters stored in different spaces are constructed respectively, and finally the exploit code is obtained by using the constraint solution. The automatic verification of format string vulnerability is realized. The experiments with different test programs under Linux system verify the effectiveness of the method.

Abstract:Aimed at the problem that communication bandwidth is limited in wireless sensor networks, a distributed Kalman consensus filtering algorithm is designed based on eventtriggered strategy. The transmission mechanism of sendondelta is adopted. Each sensor sends its own observations to the corresponding estimators only when the square of difference between the current observation and the latest sent observation exceeds a tolerable threshold. In addition, each estimator can receive estimates from its neighbor nodes through timetriggered rules. In order to avoid the calculation of crosscovariance matrices between estimators, an eventtriggered distributed Kalman filter is proposed by locally minimizing an upper bound of the variance. The exponential boundedness of the algorithm in the sense of mean square is proved by the Lyapunov method. The numerical simulation shows that the less the eventtriggered threshold value, the greater the communication rate, and the higher the estimation accuracy of the proposed filter. Otherwise, the lower the communication rate, the lower the estimation accuracy.

Abstract:Aimed at the problems that population diversity is weakening and easy to fall into local optimization in the late iteration by sparrow search algorithm (SSA), a chaos sparrow search algorithm is proposed based on hierarchy and Brownian motion (CSSAHB). Firstly, chaotic map is introduced for adjusting the key parameters of SSA. Secondly, a hierarchy is introduced. The three best individuals of the parent population are used to update the position of the vigilantes, enhancing communication among individuals and increasing population diversity. The uniform step controlled by Brownian motion is used to enhance the exploration ability of the algorithm. When the algorithm is stagnant, the Brownian motion strategy is used to disturb the individual to urge the algorithm to get rid of the local optimum. Finally, the greedy strategy is used to retain the dominant individuals and effectively accelerate the convergence speed. 12 test functions are made by the simulation experiments. The results show that the chaotic maps can enhance effectively the performance of the algorithm, and make the iterative maps perform the best. The improved algorithm is stronger in local optimum avoidance ability, faster at convergence speed, and higher in convergence accuracy.

Abstract:In the distributed storage system, locally repairable code can improve repair efficiency when a node is at fault. Quaternary distance optimal codes are easy to realize and their errorcorrecting ability is superior to that of the binary distance optimal codes when code length and dimension are given. However, there are lots of work needed to construct quaternary locally repairable codes by quaternary distance optimal codes. When the dimensions of quaternary distance optimal codes are 2≤k≤4, by combination with the operation of combination, such as extension, the deletion and the juxtaposition, the paper can obtain generator matrices of quaternary Simplex code, MacDonald code and few distance optimal linear codes to construct quaternary locally repairable codes with code length n≥k+1 and small locality, and can verify quaternary locally repairable codes to attain SingletonLike bound or CadambeMazumdar bound and prove that except for 55 quaternary locally repairable codes, other quaternary locally repairable codes are all locality optimal.