Abstract:Mobile ad hoc network is a communication network formed by mobile nodes with non-infrastructure, which has highly dynamic characteristics. Conventional routing protocols cannot adapt to the frequent topology changes brought by node mobility, and the flooding routing also causes the network performance degradation due to the excessive routing overhead. A stepwise routing algorithm based on reinforcement learning was proposed for adaptive routing in mobile ad hoc networks. This algorithm aims at total round trip time minimization and uses the reinforcement learning algorithm to select the next hop. After selecting the set of nodes that meet the requirements of the target, it combines the confidence parameters to select the route. When the link becomes unreliable, packets are broadcasted to filtered neighbor nodes to improve the reliability and reduce the routing overhead. The main property indication of the proposed algorithm, such as throughput and routing overhead, were analyzed theoretically. The simulation results show that, compared with the reinforcement learning based smart robust routing, the proposed routing algorithm reduces the overhead and maintains a competitive throughput.

Abstract:OFDM (orthogonal frequency division multiplexing) is an essential technique in the physical layer of wireless communications, and OFDM system requires rigid orthogonality between subcarriers. However, in practical systems, the imperfection of components like the oscillator and filter would introduce IQ(in-phase and quadrature-phase) imbalance into the system. The IQ imbalance would infect the orthogonality between subcarriers and decrease the system performance. The effect of IQ imbalance was discussed and an IQ imbalance compensation algorithm with the guidance of parallel DNN (deep neural network) was proposed. The deep neural network relies rarely on mathematic models, and the proposed algorithm utilizes this feature to recover the original signal from the received signal in the frequency domain to its original binary sequence of transmitted signal directly. Meanwhile, the prior knowledge that the interference comes from the image aliasing effect was utilized to initialize the model-driven neural network. Simulation results proves that the proposed algorithm can effectively compensate IQ imbalance distortion, and it outperforms traditional LS algorithm based on pilots in both amplitude and phase compensation and proves the superiority of deep learning solutions for issues in the physical layer.

Abstract:In cognitive radio system, the secondary users learn radio spectrum environment through spectrum sensing to get the spectrum holes that the primary users do not occupy. In practice, the existence of various malicious attacks can seriously affect the reliability of spectrum sensing of the secondary users. Only in-depth study of the malicious attack strategies can ensure the security of cognitive radio networks. Based on this, a spoofing jamming strategy in cognitive wireless network, called as primary user emulation attack strategy, was studied. The strategy deteriorates the spectrum sensing performance of the secondary users by transmitting the forged primary user signals over channels. More concretely, the attack strategy was modeled as an online learning problem, and a Thompson sampling based attack strategy was proposed to find an efficient tradeoff between the exploitation of high-performance channels and the exploration of uncertain channels. The simulation results show that compared with the existing attack strategy, the proposed attack strategy can better adapt to the non-stationary cognitive wireless network by optimizing the attack decision through online learning.

Abstract:In order to adjust the parameters of cell antennas dynamically according to the real-time coverage in the new generation mobile wireless network, it is necessary to predict the wireless coverage efficiently and accurately. The traditional solution method is to judge the antenna parameters by accurate field strength prediction in the target area. The method is accurate but wastes large amounts of computing resources, which cannot meet the actual needs of 5G and beyond 5G mobile networks to dynamically adjust the radio frequency parameters through real-time coverage prediction. Here the algorithm based on deep neural network was proposed to predict the coverage under given antenna parameters in order to replace the accurate field strength prediction of the target area. Numerical results show that the algorithm can keep the accuracy of the calculation while significantly reducing the computing resources, which provides basic reference data for 5G dynamic network planning.

Abstract:Dynamic spectrum access is deemed as an effective solution to the radio spectrum scarcity and spectrum usage in efficiency problem, which allows secondary users to access the spectrum dynamically for data transmission when the licensed spectrum is idle. However, spectrum sensing is one of the key challenges for dynamic spectrum access. Since the secondary user was equipped with limited sensing capability, in order to obtain more spectrum access opportunities, the spectrum sensing order problem was investigated to find the frequency band with the highest probability of being idle as soon as possible. Considering that the probability of the spectrum being idle was not available for the secondary users and changes over time, an online learning framework in which the spectrum sensing order problem was formulated as a classical multi-armed bandit problem was proposed, and it was addressed by using an online learning method, referred to as satisficing discounted Thompson sampling. Simulation results indicate that compared with other algorithms, the proposed algorithm yields more spectrum opportunities and can track the changes of the probability of the spectrum being idle.

Abstract:With the rapid development of network applications, the Internet traffic classification has a profound impact on the research fields of network resource allocation, traffic scheduling and network security. The traditional flow analysis method based on machine learning has strict requirements for the feature selection and distribution of network flows, which makes it difficult to accurately and stably classify the complex and changeable flow data in practical application. In order to solve the adverse impact of the complexity of sample features on the traffic classification, a new classification method based on deep forest, which utilizes the cascade forest of decision trees and the multi-grained scanning mechanisms aiming to improve classification performance in the case of limited scale of samples and features, was proposed. The machine learning algorithms including support vector machine, random forest and deep forest were trained and tested by using Moore, which is a flow data set in public domain. The experiment results show that the classification accuracy using deep forest model reaches 96.36%, which outperforms the other machine learning models.

Abstract:A real-time detecting and updating search strategy was presented for UAV area target search in uncertain environment, and an optimal configuration method of airborne photoelectric load parameters was proposed. An area target search model based on a two-dimensional discrete grid was established, and a probability map was used to describe the real-time acquisition and update of target information. A search objective function was built with the introducing of uncertainty index, revisiting of grid with target and controlling of grid detection times. The search route planning method based on particle swarm optimization was established. Through the estimation and analysis of average detection time and misjudgement probability of the task area, the optimal configuration strategy of airborne photoelectric load parameters was proposed. The Monte Carlo method was used to verify the effectiveness of the area target search method and the effect of photoelectric load parameter configuration on search efficiency and misjudgement probability.

Abstract:The PROD (precise relative orbit determination) for the LEO (low earth orbit) formation-flying satellites based on BDS (BeiDou satellite navigation system) was studied. Due to the lack of experimental data, the simulation method was used. Results show that the average number of visible BDS satellites at altitude of 500 km is about 9.7. Because of the GEO (geostationary earth orbit) satellites and IGSO (inclined geosynchronous earth orbit) satellites, the LEO satellites can observe more BDS satellites over the Asia-Pacific region. When only the observation noise is considered, the accuracy of PROD based on BDS is 0.74 mm. Furthermore, the influence of ephemeris errors is analyzed. For a few kilometres separation of the LEO satellites, the effect of ephemeris errors on PROD could be ignored. However, for a 200 km separation of the LEO satellites, the SD (single difference) ephemeris errors of GEO satellites would be on the order of centimetres. The experimental results show that when IGSO satellites and MEO satellites co-work with GEO satellites, the accuracy decreased from 1.09 mm to 0.96 mm, decreased by 13.54%. Finally, the conclusion is that the accuracy of PROD based on BDS can reach sub-millimeter level after the remaining errors are processed, the differences of the PROD results are not apparent between different regions. When relative position between satellites is only a few kilometres, the GEO satellites and IGSO satellites can improve the accuracy of PROD all over the world. In the future, BDS will be widely used in PROD of LEO satellites.

Abstract:Bolted flange joint is widely used in most kinds of industrial structures. In order to indicate the static or dynamic response accurately, an exact and efficient finite element model needs to be built. For the parameters are not certain when building the model, the numerical simulation and experiment were synthetically employed to study the determination of the model′s mesh parameters and contact parameters. After confirming the parameters, the finite element model of bolted flange not only has high computational accuracy, but also has ideal computational efficiency.

Abstract:Creep is an important characteristic of near space aerostat′ s envelope material. A creep test bench was designed to test the creep characteristics of a typical envelope material for near space aerostat, and the creep data of the material at atmospheric temperature were obtained. Based on the creep model of general polymer materials and the creep data obtained from the test, the creep calculation model of aerostat materials was analyzed, and the relevant parameters were fixed. Also, the creep variables of aerostat materials were simulated with the method of finite element analysis. Furthermore, the veracity of the creep model and the simulation analysis for DPE-3 thin film was verified by comparing the creep variables calculated by the creep model, the creep variables analyzed by the finite element simulation and the actual creep variables were obtained by the creep test. The creep test method and the results of calculation and analysis can provide a reference for the design and analysis of aerostat in near space.

Abstract:Due to serve under the environment of high temperature and high humidity, hygroscopic aging behaviors are commonly discovered in adhesively bonded composite repaired metallic aircraft structures, which results in the decrease in mechanical properties and server life. In order to investigate the effect of hygroscopic aging on adhesively bonded composite repaired structures, moisture absorption and aging test were performed on adhesively bonded composite repaired aluminum alloys plates containing double-sides cracks with single patch and E44/Polyamide epoxy resin, then the effect of hygroscopic aging on load carrying capability, crack propagation life, repaired effect and duration of fatigue load were analyzed by the experimental method and finite element method (including damage zone theory and J-integral ). Results show that hygroscopic aging lowers the load carrying capability and fatigue crack propagation life greatly, with the result that the average value of fatigue crack propagation life and ultimate load of repaired structure decreases by 29% and 10% respectively after immersing in water for 40 days, and the failing mode of adhesive changes into interfacial failure from cohesive failure. After immersing in water for 30 days, the adhesive specimens became completely plastic, whose elastic module decreases by 60%, and plastic deformation increases to 25%. The effect of hygroscopic aging on the damage zone was obvious, which results in the fast damage of adhesive, and the longer the crack is, the faster the damage is. The hygroscopic aging of repaired structure also increases the value of J-integral around the crack tips, which decreases the crack propagation life of repaired structures.

Abstract:Aiming at the problem of the limited application scope of water-pulley model, a method for smoothing the tug track to obtain the track of the sonar array and estimate the array shape was proposed. By analyzing the steady-state vibration response characteristics of the array, it is considered that each point on the sonar array moves along the same track. The smoothing window was designed to smooth the tug track into the track of sonar array during circular maneuver, and was extended to the scene of course-change maneuvering. A part of the window was used to smooth the track portion, whose distance from the tug is less than the width of the smooth window, to obtain the current cable shape, so as to estimate the shape of the whole array during the course-change maneuvering. The simulation results show that if the array consists of 81 elements spaced at 5 m, the proposed method can increase the average array gain during course-change maneuvering by about 0.8 dB and lower the average direction estimation error by about 4.7° compared with the original water-pulley model. Using the simulation results to analyze the input sensitivity of the algorithm, the proposed method was simplified to make it easier to implement. Verification using sea trial data shows that the simplified method is feasible and effective.

Abstract:In order to overcome this defect of traditional magnetic target motion estimation′s dependence on the initial state information of the target, a three-axis projection model of magnetic moving ship targets was established, and 10 kinds of target training datasets, validation data sets and test data sets of magnetic ship moving targets with variable parameters were generated. Multi-channel convolutional neural network was designed to estimate the distance abeam and velocity of the target, and the effects of different learning methods and activation functions on the performance of the network were compared and analyzed. The results show that the performance of Adam+tanh method is better than other methods, and the estimation effect of motion parameters is accurate. Compared with Kalman filter and particle filter, this estimation algorithm is calculated with preferable efficiency and independent of initialization for estimation.

Abstract:Because the air wake fields of large ships have a great influence on the safety of aircraft landing, therefore, the effective technologies to guarantee the safety of aircraft and maritime activities are of great significance. The CFD(computational fluid dynamics) method was used to study the air wake field characteristics of large ships and the prevention and control technologies. The Reynolds averaged Navier-Stokes equations with Spalart-Allmaras turbulence model were used to construct simulation platform, the numerical modeled work was carried out through the platform. The regular and characteristic of air wake fields of large ships were analyzed. Furthermore, the new prevention and control technologies of air wake field of large ships were proposed, and the theoretical basis, center method and technical proposal were expounded. According to the thinking and theory of active blowing prevention and control technology, numerical modeling method was used to test the new prevention and control technologies of air wake field of large ships. Numerical results show that the new method can significantly improve the quality of the air wake field, make the flow field stable and uniform, and hence it can reduce the impacts on the aircraft landing on large ships. After the method is further improved, the engineering application can be realized to ensure the safety of aircraft landing on ships, potentially.

Abstract:Compared with other cathodes, LaB₆ cathode has the advantage of high electron emission current density, and has been widely used in electric propulsion, high emission density electron gun and other products. In order to analyze the poisoning characteristics of the LaB₆ hollow cathode and identify its failure mode, the performance change features and reasons of LaB₆ hollow cathode exposed to atmosphere were studied. The results show that the LaB₆ hollow cathode adsorbs a great deal of poisonous gas on the surface of the emitter during exposure to the atmosphere, and while the work function from the emitter surface increases, the emitter appears short-term poisoning phenomenon. The discharge voltage and hollow cathode plate temperature are increased, and the discharge voltage and cathode top temperature are restored to the initial state after short-term operation. However, if the poisoning phenomenon of LaB₆ hollow cathode is serious, the oxide generated on the surface can not be removed by heating and ion bombardment. Therefore, the emitter state of hollow cathode can be indirectly characterized by monitoring the change of cathode temperature and anode voltage during the test.

Abstract:The sensor-weapon joint task management under dynamic environment was studied. The stage threshold, which determines the beginning of next stage, was set according to the number of valid newly appearing targets, idle sensors and weapons during the dynamic combat process. The multi-stage combat process was constructed. The effect of distributed combat system to the quality of attack scheme and the response time of system was analyzed. As a result the system could decide the response flow of each task management stage independently. The superiority of constructing distributed combat system and setting the stage threshold was verified by simulations.

Abstract:Based on the status quo of modularization of equipment design, the evolution of equipment structure and the order of importance ranking by using importance theory were analyzed. On the basis of the gradual evolution from single component to five-component structure and N-component series-parallel structure, the evolution law was sorted out, and the importance analysis of the typical structure was carried out. The evolution of equipment structure and the order of importance of each component are obtained, which fills in the blank of the research on the importance drift law of the equipment, and provides technical support for the reliability optimization design of the equipment.

Abstract:Aimed at the problem that the smoothing accuracy of Hatch filter in single frequency GBAS (ground based augmentation system) is reduced by the ionospheric anomaly, the influence of ionospheric delay on the smoothing accuracy of Hatch filter was analyzed systematically, and an improved adaptive Hatch filter algorithm was proposed. The code-carrier divergence was calculated according to the satellite signal, and its high frequency was suppressed by using the second-order linear time-invariant filter to detect whether the ionosphere is abnormal. A function model between the root mean square of smoothed pseudorange error and the ionospheric delay rate, the standard deviation of pseudorange measurement noise and the smoothing time was established, from which the optimal smoothing time of Hatch filter was determined. The verification experiments were carried out by using GBAS prototype developed in the laboratory. The experimental results show that the adaptive Hatch filter algorithm is able to calculate the optimal smoothing time according to the ionospheric delay rate of satellite signal. When the ionospheric is abnormal, the maximum airborne position error is reduced from 1.15 m to 0.43 m, which verifies the effectiveness of the proposed algorithm.

Abstract:Owing to the low accuracy and poor real-time ability of modern air combat maneuver decision-making, the BAS-TIMS (beetle antennae search-tactical immune maneuver system) algorithm was improved and applied to air combat maneuver decision-making. The traditional maneuver inventory was enlarged by adding four maneuvers, left climbing, right climbing, left diving, right diving. Eleven basic maneuver tactics were designed, and a method was given to control them. Considering range, height, speed, angle and the superiority function of fighter performance, a comprehensive superiority function of fighter performance was built with the help of nonparametric model. Monte Carlo probability iteration was introduced into the beetle antennae search algorithm to improve its global search ability and convergence speed. This algorithm was combined with TIMS, and the improved BAS-TIMS algorithm was applied into modern air combat maneuver decision-making. An example was given to simulate and prove the effectiveness by comparing BAS-TIMS with game theory, the improved symbiotic immune evolutionary algorithm, the traditional BAS algorithm and the traditional TIMS model. The simulation results show that the improved BAS-TIMS algorithm has more advantages on convergence speed, accuracy and global search ability in air combat maneuver decision-making.

Abstract:The quantum algorithm which was put forward recently has led to great insecurity of cryptographic analysis of the coding under quantum computing. The future of the code-based cryptography with anti-quantum attack properties was questioned by many people. However, in the research process, people gradually had a deep understanding of the advantages and disadvantages of its encryption scheme. At present, the code-based cryptography has become one of the most promising post-quantum cryptography schemes. The code-based encryption schemes were summarized and the existing attacks of their original schemes were analyzed. Finally, the nature of the security problem of encoding-based encryption system is analyzed, and the future development direction is expounded.