Abstract:In order to enable the UAV to effectively avoid the sudden threat of the ground fire, this paper studies and uses the cognitive decision of human intelligence. By analyzing the ground attack process of UAVs, a ground attack model is established, and the maneuver behavior of UAVs during ground attack is summarized into three ways. The three way decision theory is to utilize the cognitive thinking of human brain for describing. A three way decision making method for cognitive decision making of UAV ground attack is presented. Through comparative analysis and simulation experiments with other types of autonomous attack decision making methods, the method enables the UAV to reasonably evade the threat of an air defense fire unit that suddenly appears during the attack process.

Abstract:In view of solving how to dynamically allocate multiwave firepower for aircraft under limitation condition of fire one-kick releasing, this paper establishes a dynamic fire distribution multi-objective optimization model (DWTA) based on the linking up with the target value, target threat, and fire distribution. A number of sub-firepower distribution models (SWTA) are included under the DWTA model, and the SWTA of the next wave is updated by the hitting effect of the previous wave SWTA as an input. The multi-object decomposition evolutionary algorithm (MOEA/D) of the hybrid conjugate gradient method is improved. Gaussian disturbance is added to generate the initial search point set, and the conjugate gradient method is used to search. The algorithm is used to solve the model. The simulation experiments show that the convergence speed of the algorithm is improved under condition of retaining the advantages of the MOEA/D algorithm. Compared with the traditional MOEA/D algorithm. tine is 22 s by using the traditional MOEA/D algorithm and only 14 s by using the modified MOEA/D algorithm, completing the dynamic allocation of multi-wave firepower.

Abstract:Path forecasting for air strike aircraft is one of the assistant methods in assessing the schemes of the deployment of air defense forces. A model of path forecasting is built based on analyzing the path forecasting problem for air strike aircraft. Then a path forecasting algorithm by evolving waypoints is presented. The methods of path forecasting by using traditional evolutionary algorithms (EAs) can hardly exploit the high quality waypoints in previous candidate paths for further evolution, since they regard all the waypoints of a path as an integrated individual. The proposed algorithm improves the framework of the traditional EAs and evaluation functions to evaluate and evolve waypoints separately. The waypoints are evolved with JADE, a state-of-the-art variant of the differential evolution (DE) algorithm, and evaluated and selected by using a multi-criteria handling method based on the priorities, exploiting high quality waypoints. To test the capabilities of the new algorithm, 4 scenarios with 15, 30, 60 and 120 obstacles are constructed respectively. The simulation results show that the proposed algorithm meets the needs for the path forecasting for air strike aircraft effectively, and its performance is previous to the genetic algorithm-based path forecasting algorithm in the scenarios with lots of obstacles.

Abstract:Aimed at the problems that the width of taxiway, the separation between taxiways and other fixed objects of the flying area fails to meet the standard requirement and the risk of aircraft operation, this paper analyzes the route deviation caused by aircraft during taxing. Based on the extreme value theory, by using the main principle of generalized Pareto distribution, the high tail of the data is analyzed, the appropriate threshold is selected and the exceed threshold model is established. On this basis, the selection of the data base sample is analyzed. Then, the paper determines the appropriate threshold and tunes the model parameters, and finally the taxiway deviation probability distribution is given. By running the taxiway deviation risk model.

Abstract:Researches on how to add the high strength synthetic fibers in the pavement concrete at the airport to improve its performance, and the impact resistance improvement of the high strength synthetic fibers at the airport pavement joints. The restructured concrete pavement rut testing machine is adopted to take the wheeled impact test in the study. Moreover, the shedding concrete quantity is used to measure the degree of injury. The test specimens are divided into two groups, i.e. specimens without staggered steps and with staggered steps. The actual situation of the airport pavement joint is simulated. The results show that as for the two test groups, an increase in the number of impact load will cause the increase of concrete weight loss. As for the specimens without staggered steps, after 1 000 times of impact, the amount of shedding concrete dropped by 1.4 kg/m3 is 51.1% lower than that of ordinary concrete. For the specimens with staggered steps, the concrete shedding decreases by 73.3%, 72.5%, and 46.6% respectively with the increase of fiber content to 1.4 kg/m3. The result shows that the increase of the synthetic fiber content can effectively reduce the shedding quantity of the joint angle and the angle at staggered steps, and the improvement effect is more and more obvious.

Abstract:Based on the ROS robot operating system and its included function package, this paper aims at the development of cell robot , and the inertial measurement elements, laser radar and the monocular camera on the cell module are used to determine the position and posture information and the surrounding environment information, and the cell robot reconstruction operation is completed. In reconstructing the Gazebo simulation reconfiguration platform, the algorithm of self positioning, map building, path planning, autonomous navigation and visual attitude adjustment are verified through the reconstruction of cell robot, and the reconstruction of different kinds of cell modules and the reconstruction of organ level are completed. The self-assembly of cell robots is realized according to the configuration of task planning. The reconfiguration scheme is feasible.

Abstract:An infrared absorber based on Au/VO2 structure is designed in this paper. This tunable meta-material absorber consists of three individual layers of resonating patch, sandwich dielectric layer, and metallic background. Using the temperature-controlled phase change characteristics of VO2, some of the Tian-shaped Au structure is replaced by VO2, and the absorption peak, position and bandwidth of the absorber can be controlled by changing the ambient temperature. Because of the thermo-control phase transformation property of the VO2, the absorber is characteristic of different absorption effects at different temperatures. When the temperature is higher than the phase transition temperature, the absorber can form an absorption peak of 99.68% in the far infrared atmospheric window; when the temperature is lower than the phase transition temperature, the absorber can form two absorption peaks with absorption rates of 89.29% and 99.83% respectively in the middle and far infrared atmospheric windows. This paper analyzes the absorption mechanism of the absorber based on the surface current distribution and the surface magnetic field. From the mentioned above the paper finds that the anti-parallel distribution of surface current excites a magnetic dipole, which generates a strong magnetic resonance, achieving the effect of absorption. In the end, this paper researches the effect of electromagnetic wave polarization mode, incident angle and media material properties on the absorption properties of the absorber. The results show that the absorption is insensitive to polarization mode and incident angle. What's more, The absorption peak shifts its way in long wavelength direction with the increase of the dielectric constant.

Abstract:Aimed at the problems that the reader communication with tags is carried out in insecure wireless channel in the radio frequency identification system, and with the emergence of mobile reader terminals, this makes the communication between the reader and the server unsafe, vulnerable to impersonation attack, eavesdropping attack, middleman attack and other security threats, a two-way authentication protocol for radio frequency identification based on Chinese remainder theorem is proposed. The symmetric encryption and modular operation ways are used to improve the security of information transmission, and the timestamp is adopted to resist the middleman attack in the protocol, and the Chinese remainder theorem is utilized for certificating all sides. Finally, random key update method is used in the keyupdating. The protocol security is verified by formal proof method and routine attack analysis. The protocol of this paper is compared with other protocols in terms of security, calculation and storage. The results show that the protocol is high in security, less in calculation and moderate in storage, and has certain application value in the security field of radio frequency identification.

Abstract:The capacity degradation of Lithium battery is influenced by excessive factors and the mechanism is complex, and the remaining useful life (RUL) is very difficult to predict. The particle filter (PF) is one of the main stream methods in the current RUL prediction research because of its excellent non-linear non-Gaussian characteristics. However, the PF has a problem of particle degeneration in nature, which weakens the precision especially when the model has a dramatic trend of changes. In order to overcome the above problems, the PF is improved by introducing the renewal philosophy of particle swarm optimism (PSO) to reassign particle weight by optimizing the global position of particle. The simulation results reveal that compared with the original PF, a more precise prediction of the RUL can be obtained with the 33.6% reduction of error, and an alleviation of particle degeneration is reached for the 18.3% reduction of resampling rate.

Abstract:Aimed at the problems that varieties of feature vectors extracted from the image is stacked into a highdimensional feature vector for image semantic segmentation, and these lead to the weakening or loss of the classification ability of some feature vectors, an image semantic segmentation method based on deep convolution neural network AlexNet and conditional random fields is proposed. The pretrained AlexNet model is utilized for extracting image features, and then the semantic segmentation of the image is achieved through the efficient use of conditional random fields for multiple features and context information. The experimental results compared with the methods using the traditional classical features show that Conv5 is the most effective feature extraction layer when AlexNet model is used to extract features for image semantic segmentation. The recognition accuracy in the Stanford background and Weizmann horse datasets is respectively 81.0% and 91.7%, and both the accuracy rates are higher than that of the two comparison methods, indicating that the deep convolution neural network can extract more effective features and obtain higher semantic segmentation accuracy.

Abstract:In order to enhance the robustness of longtime visual tracking, an improved TLD algorithm based on image perception hash is proposed. In the improved algorithm, scale adaptive KCF used is a tracker of the tracking module, the detection module is used to extract the perceptual hash feature from each detection window, and quantum genetic algorithm is taken as a search strategy to accelerate the detecting speed. A tracking performance test is conducted with 50 video sequences provided by the OTB2013. The experimental results show that the tracking precision and the success rate of the method reach 0.784 and 0.568 respectively, and increase by 18.7% and 14.2%, compared with the TLD algorithm correspondingly. Besides, in most cases, the proposed algorithm performs better than the reference algorithm in the presence of illumination variance, occlusion, low resolution and other complex situations.

Abstract:In view of the registration between LiDAR data and aerial image fusion, this paper presents a registration method combining surface feature and point feature. Firstly, the depth image is generated by LiDAR point cloud, and the surface feature is extracted from the depth image and aerial image. On the basis of this, the SIFT operator is used to extract the point features for the registration of LiDAR point cloud and the aerial image. This method adopts a registration strategy from the surface features to the SIFT features, reducing the amount of data for registration of features and the computational complexity of SIFT algorithm. In this paper, three sets of data are selected from the data set provided by ISPRS.The experimental results show that this method can effectively reduce the number of feature descriptors of SIFT operator and the time of finding the correct matching point, and improve the registration efficiency under condition of ensuring the registration accuracy. This is applicable to LiDAR point cloud and aerial image registration including large area of feature area in urban area.

Abstract:In order to predict the failure of Darlington transistor, a method for fault prognostics based on KPCA and Mahalanobis distance is proposed. Through the failure mechanism analysis and accelerated degradation testing of Darlington transistor, the degradation data of collector current and saturation voltage are obtained. The paper utilizes wavelet packet decomposition and KPCA to process the degradation data and filter out interference signals, obtaining the principal component of the degradation. The Mahalanobis distance is used to fuse these components into health index. And the health index could represent the healthy status of Darlington transistor in changes. Finally, two fault predict algorithms are used to predict the HI. And the availability is proved by the forecasting. The results show that RMS between the predicted value and the true value is within 10%.

Abstract:In order to more accurately master the laws of network security situation regular and prevent some network security threats, in view of the problem of parameter selection of Support Vector Machines, plus, the gravitational search algorithm (GSA) is characterized by few parameters needed and having great ability in global optimization, a network security situation prediction model (GSASVM) is proposed for GSA optimization SVM parameters. First, the parameters of SVM are treated as objects in space, and mean square error (MSE) of predicted value and actual value of SVM under this parameter is used as the objective optimization function, then GSA can find the optimal parameters of the SVM by simulating the law of gravitation, and finding the optimum parameter eventually. Finally, a network security situation prediction model is established according to the optimal parameters. Using DARPA 1999 data set provided by MIT Lincoln Laboratory in MATLAB platform, the simulation results show that GSA-SVM improves the accuracy of network security situation prediction and accelerates prediction of network security situation relative to other prediction algorithms. This provides a new way to solve problem of network security situation prediction.

Abstract:In order to reduce the effects of interference polarizations on sidelobe cancellation system, this paper proposes an antijamming method in spacepolarization domain based on dual polarization auxiliary antenna and Kalman filter. The paper transforms the auxiliary antennas into dual polarization and selects the polarized signal by auxiliary channel power, and then uses the Kalman filter and the selected signal channel to cancel the sidelobe jamming in main antenna channel . In this method, the side-lobe canceller system is regarded as error prediction filter; the optimized auxiliary channel output is weighted and added as the measurement; the weight vector is modified iteratively to reduce the error of the measurement and main channel signal, eliminating the side-lobe interference and improve the signal-to-noise ratio of main antenna channel. The simulation results show that the convergence speed and stability of this method are better than that of the conventional side-lobe cancellation algorithm, and the method applies to multichannel. The output SNR of orthogonal polarization interference is better than that of the conventional SLC of about 10 dB, and the stability is fine with low sampling points.

Abstract:Taking an active radar missile countermeasure as background, this paper studies the single-platform airborne electronic countermeasure (ECM) scheduling problem. In order to solve the uncertainty problem of missile seeker state observation, the partially observable Markov decision process (POMDP) theory is introduced. The elements of POMDP model are analyzed, an optimization model of ECM resources is established for the active radar homing missile, and the solution is solved by successive approximations of the reachable space under optimal policies (SARSOP). A new real-time scheduling optimization algorithm for ECM resources based on POMDP is presented, combined the output of electronic support measure (ESM) with the control strategy of ECM together. The simulation results indicate that the proposed algorithm can realize effective scheduling of ECM resources under the situation where the target state is uncertain compared with the existing approach, the radar missile will stay in seeoch state more and stable tracking state less.

Abstract:Focuses on the construction of low-dimensional optimal LCD codes overF5 on the basis of the theory of optimal codes, projective geometry in view of the characteristic of the distance of optimal codes. First, via some known and puncturing, the paper constructs a shortdistance optimal and optimal LCD codes of dimension 3 and 4. Then the theory of projective geometry is used to construct those codes with long-distance. Moreover, with the combination of the known optimal LCD codes and optimal self-orthogonal codes, the paper can construct any long-distance optimal LCD codes. With these methods, all the optimal LCD codes of dimension 3 and 4 can be solved. The theories and methods of constructing LCD codes have a certain of important guiding significance for the study of high-dimensional optimal LCD codes over F5 and those over general field.

Abstract:A subclass of *inverse semigroups is in vestigated in this paper, namely, U*inverse semigroups. Besides, the paper gives that a semigroup is an U*inverse semigroups if and only if for any x∈S there exists a unique element x0∈H*1 such that x≤x0. Moreover, the paper proves that an U*inverse semigroups is F-Abundant semigroups if and only if, M=H*1，so that L*inverse semigroups and F-Abundant semigroups are connected.