Abstract:In order to reasonably evaluate the primary gas/air mixing combustion process in the secondary combustion chamber of solid rocket ramjet, an evaluation method of mixing combustion process of solid rocket ramjet based on particle mass concentration was proposed. Numerical simulation method of engine was established and verified by ground test. Aiming at the mixing combustion process in the afterburner under different working conditions, the changing trend of mixing degree and combustion efficiency in different definitions was compared by numerical simulation. Results show that the proposed particle mixing degree and particle combustion efficiency shows the greatest correlation, and the average maximum information coefficient reaches 0.916 3 under different working conditions. Moreover, the primary gas/air mixing and combustion process shows the following correlation laws:the particle combustion efficiency increases with the increase of particle mixing degree, and when the particle mixing degree exceeds a certain threshold, the particle combustion efficiency remains relatively stable. And the law is verified by experiments.

Abstract:Frost formation on the air side of the heat exchange channels of the precooler has an important effect on the overall performance of the precooled engine. Condensation/frosting process of three kinds of specimens with irregular surface topography structure (Ra=0.97 μm, Ra=1.78 μm, Ra=1.92 μm) in high temperature environment(T_a=50 ℃) was studied experimentally. The effect of the ambient temperature(T_a is 50 ℃ and 18 ℃), surface temperature (T_w is -10.9 ℃, -23.0 ℃, -28.0 ℃) and the irregular surface structure on frost crystal/condense droplet growth characteristic were studied. The densification mechanism of the frost layer was summarized and analyzed. The experimental results showed that the higher the ambient temperature, the lower the surface temperature, and the shorter the frost crystal growth cycle. On the surface of the three specimens, the closer to the edge of the specimen, the earlier the condensation droplets appeared and the faster it grew. Besides, it was also found that the surface morphology and structure have influence on the whole process of droplet condensation and frost layer growth. The mechanism of the surface topography structure on condensation was preliminary analyzed, but the mechanism of irregular surface topography structure on frost growth needs further study.

Abstract:Aiming at the problem that the soft insulator of pulse motor can not accurately describe its state and regular in the actual working process, a soft insulator opening test system was designed, which approximately simulated the working process of the soft insulator in the pulse motor. The opening characteristics of the ablative and non ablative soft insulator were compared, and the deformation law of the ablative and non ablative interlayer from the mechanism was explained by the means of scanning electron microscope. The test results show that the ablation rate calculated by the ablation simulation test is approximately equivalent to the insulator of a test pulse motor, and the relative error can be controlled within 5%; the deformation of the non ablated insulator is “valley pile” and the deformation of the ablated insulator is “bulb”. The established soft insulator layer opening test system can provide a feasible technical approach and means for the design and test verification of the soft insulator of pulse motor.

Abstract:To deal with the problem of the existing telemetry anomaly detection algorithms, such as the poor discrimination capability of the feature, and loss of anomaly decision-making information, a self-ensemble anomaly detection method based on center-constrained contrastive learning was proposed. The method mapped the normal samples to a compact feature distribution by combining contrastive loss and center loss, and a multi-view and multi-level ensembled feature decision method was used to obtain the anomaly detection of the sample. The method improves the adaptability of the model to the complex working conditions of the satellite. The real telemetry parameter data of scientific satellite and benchmark data set are used for verification. The proposed method is robust to noise, and achieves 21.8% improvement of F score than that of the state of the art method. The results of the experiment demonstrate the feasibility of the method, which can provide effective support for satellite operation.

Abstract:It was difficult to balance the efficiency and accuracy of multi-mode life RBDO(reliability-based design optimization) of turbine blades with film holes in the presence of random uncertainty, a quasi-sequence decoupling method of RBDO based on adaptive Kriging surrogate model was proposed. The construction process of the limit state surface surrogate model in reliability constraint was updated in real time with the search iteration of the design parameters, and the surrogate model strictly ensured the accuracy of surrogate model and feasible region judgment in each iteration step. The proposed method avoided updating the limit state surface in non-access domain of design parameters, so that obtaining a high convergence speed and strong robustness. The embedded real-time update strategy builds a cooperative surrogate model in the extended space and shares training sample points, and adaptively trains the Kriging model of the objective function until convergence, so that it is able to ensure the surrogate accuracy and significantly improve the optimization efficiency. In addition, an integrated and automatic simulation system for life reliability optimization is developed, which verifies the high efficiency and engineering feasibility of the proposed method and software in the turbine blade life RBDO problem.

Abstract:A new star map identification method was proposed to solve the problem of space lost of star sensor. The distance mapping vector was used to calculate the dispersion between the reference star and the navigation star, in order to shorten the list of the navigation star database and obtain the candidate navigation star. The angle feature vector and the distance feature vector were used to match the unique corresponding navigation star of the reference star through the similarity calculation. The feasibility of this method was evaluated by the performance test of simulated star map and real star map. The results show that the proposed method is robust to noise and can guarantee the recognition rate of more than 93.80% under the influence of harsh environments such as location noise, pseudo stars and missing stars.

Abstract:To deal with the problem that multiple missiles cooperatively attack maneuvering targets with impact angle constraints, a novel leader-following missiles fixed-time cooperative guidance law was proposed. The leader-following missiles cooperative guidance model was established according to the relative motion between the target and missiles. Based on the fixed-time sliding mode control theory, the guidance law in the directions normal to the LOS(line-of-sight) was designed, so that the leader and followers could accurately attack the maneuvering target from the desired impact angles. Based on the consistency error function and the fixed-time sliding mode reaching law, the guidance law in the LOS direction of the followers was designed, which fully utilized the information exchange between missiles, and the time-to-go of the followers could quickly achieve consensus with that of the leaders in fixed time. Simulations and comparison verification indicate that the designed guidance law has higher control accuracy for time and angle constraints, no singularity and chattering phenomenon, faster convergence speed and the convergence time bound is independent of the initial states, which fully verifies the effectiveness and superiority of the proposed guidance law.

Abstract:In order to accurately and effectively determine the location selection of missile launch position, overcome the disadvantages of strong subjective factors and the difficulty to judge the pros and cons of the location selection scheme in the current position location process, a two-stage position location selection method based on GIS(geographic information system) and improved TOPSIS(technique for order preference by similarity to an ideal solution) was proposed. In the primary selection stage, the index system affecting the location selection of launch position was constructed, and the comprehensive weight of each index was obtained by using the improved analytic hierarchy process. Aiming at the quantitative index, the multi-loop buffer zone was established by GIS technology for spatial analysis, and the selection scheme of launch position location selection was obtained. In the precise selection stage, combined with the scores of each index of the alternative scheme, and aiming at the qualitative index, the grey correlation improved TOPSIS was used for comprehensive evaluation to obtain the optimal location scheme of missile launching position. Example verification shows that this method has good operability and applicability, and the influence of subjective factors is small, which can provide decision-making basis for the location selection of missile launching positions.

Abstract:Aiming at the problem of poor applicability of current path planning results for underwater vehicles, a three-dimensional path planning algorithm for underwater vehicles based on improved particle swarm optimization algorithm was proposed. A Voronoi map based on the real terrain data of sea area was built, and the Dijkstra algorithm was used to generate the initial path set that meets the requirements of navigation safety as the initial particles of particle swarm optimization algorithm, so the generation efficiency of initial particles was improved. At the same time, the particles′ position update method was improved to guide the particle position change according to the position of adjacent nodes on the route, which makes the planned route smoother and more suitable for the navigation of underwater vehicles. Simulation results show that the proposed algorithm is more robust and has better applicability than the traditional particle swarm optimization algorithm in path planning.

Abstract:To optimize the software implementation of the domestic block cipher uBlock algorithm, the AVX2 instruction set supporting 256 bit data width was implemented, the automatic optimization level of the compiler was increased, optimizing the calling process of functions, and the methods of data storage structure optimization, high-level parallelism and low latency instruction logic optimization were used in order to implement parallel computing under the single-thread condition. Using this efficient combination method, the speed of single key short message encryption of uBlock-128/128 algorithm, uBlock-128/256 algorithm and uBlock-256/256 algorithm are 269%, 182% and 49% higher than the original code. Based on these optimization methods,the implementation of single-key scenario and multi-key scenario are given for three algorithm versions of uBlock-128/128, uBlock-128/256 and uBlock-256/256.

Abstract:Aiming at the deficiency of traditional data imputation methods in effectively using the label information and random characteristics of missing data, a particle swarm optimization based imputation method for mixed features was proposed. The value of continuous feature was modeled as Gaussian distribution, and the mean and standard deviation were used as optimization parameters. The value probability of categorical features was optimized as a parameter. The classification accuracy rate was used as the optimization target to make full use of random information of label information and missing data. Four statistical methods and two evolutionary algorithm based imputation methods were used to compare the results on six typical classification datasets. The results show that the proposed method significantly outperforms other comparison algorithms in terms of classification accuracy indicator, and has better time overhead at the same time, which can effectively solve the data missing problems of mixed features.

Abstract:For analyzing PPP-B2b actual service performance, PPP-B2b data and International GNSS(global navigation satellite system)service data for a period of 30 days as well as offshore shipborne dynamic data on 16 December 2021 were used for evaluating orbit and clock offset accuracy and testing real-time PPP(precise point positioning)positioning performance. And compared with the corresponding results of CNT—archived products of CNES(centre national d′etudes spatiales,CNES). Results show that the radial accuracy of BDS-3 (BeiDou navigation satellite system phase Ⅲ) and GPS (global positioning system) track of PPP-B2b service are 0.07 m and 0.089 m respectively, which are below CNT 0.041 m and 0.025 m. The clock offset accuracy of BDS-3 is 0.029 m, close to GPS clock offset, better than 0.057m of CNES product accuracy. In the static positioning test based on PPP-B2b, BDS and BDS-3+GPS average convergence time is less than 20 minutes, better than that of GPS, and the convergence accuracy is higher than GPS. In the dynamic test, the RMS value of BDS-3 and BDS-3+GPS in the NEU(north, east and up)directions are better than 11 cm, GPS is better than 26 cm. In offshore positioning testing, the RMS value of BDS-3+GPS of PPP-B2b in the NEU directions are 0.028 m, 0.074 m, 0.081 m, and the convergence time is 12.4 min.

Abstract:Aiming at the problem of low detection and recognition accuracy of traffic signs in complex traffic scenes, a target detection and recognition method based on improved YOLOv5s algorithm was proposed. Iterative self-organizing data analysis techniques algorithm was used for clustering analysis of TT100K data set to select the prior frame which was more suitable for the size of traffic signs. The new prior frame could cover the size of traffic signs more comprehensively and improve the detection accuracy of the model. The feature map was upsampled to obtain a larger scale feature map, and then contacted with the feature map of the backbone network to obtain a new feature map with more abundant feature information. The new feature map was used for small target detection and recognition, which improved the accuracy of small target detection and recognition. And the difference of the width ratio and height ratio between the real frame and the prior frame was used to replace the difference of the aspect ratio between the real frame and the prior frame to improve the positioning loss function, which solved the problem of penalty disappearing when the width ratio was the same but the actual size was different. Experimental results show that compared with the original YOLOv5s algorithm, the improved algorithm can improve the mean average precision by 9.55%, and has better performance in detecting and recognizing small targets.

Abstract:In terms of the problem that SAR(synthetic aperture radar) in UAV(unmanned aerial vehicle) is easy to be attacked by HPM(high-power microwave) weapons in the complex electromagnetic environment of the battlefield, the field-circuit joint simulation of high-power microwave front-gate coupling of UAV′s SAR was carried out. Model of the SAR′s antenna was established in the CST(computer simulation technology) software. Model of antenna was irradiated with a pulse-modulated sinusoidal signal to simulate the HPM signal, and the antenna port coupling voltage waveform was collected. Antenna port coupling voltage signal obtained in the CST software was injected into the RF(radio frequency) front-end circuit model of SAR, which fully simulated the coupling process of high-power microwave signal from field to circuit. Simulation results show that the low noise amplifier in the RF front-end circuit of SAR is the main target of HPM signal damage, and the spike leakage power of the limiter will threaten the low-noise amplifier of the post-stage circuit. Through simulation, the evaluation diagram of the coupling effect of high-power microwave front door of UAV on-board SAR is obtained.

Abstract:Convolutional neural networks currently applied to radiation source identification process the time-series IQ( in-phase and quadrature-phase) signals in two ways:one way transforms them into images, and the other way extracts shallow features of the IQ time-series data. The former way leads to a large computational effort of the algorithm, while the latter way leads to a low accuracy of the recognition rate. To address the above problems, a multi-scale feature extraction and feature selection network was proposed. After inputting the IQ signal, the shallow and multi-scale features of the IQ signal were extracted by the multi-scale feature extraction network. Then the data dimension of multi-scale features was reduced by the feature selection network. Feature enhancement was achieved by the adaptive linear rectification unit, and a single fully connected layer was used to classify the radiation source. Comparison experiments with ORACLE, CNN-DLRF and IQCNet on the FIT/CorteXlab radio frequency fingerprint recognition dataset show that the proposed network improves the recognition accuracy and reduces the computational effort to some extent.

Abstract:The study of GNSS(global navigation satellite system) vertical time series is helpful for monitoring and analyzing the movement of crustal plates, and can provide an important basis for judging the movement trend. A MEMD-XGBoost model was constructed based on empirical mode decomposition and extreme gradient boosting algorithm for GNSS vertical time series prediction and analysis. In order to verify the prediction performance of the model, the vertical time series data of 8 GNSS stations were selected for prediction experiments. The feature construction results show that multiple empirical mode decomposition can accurately extract the original time series information and provide effective features. The modeling results show that the MEMD-XGBoost model can effectively improve the data quality. The prediction results show that the prediction results of the MEMD-XGBoost model have high precision and accuracy, and the degree of error dispersion is small, the model has strong stability and robustness, and can better predict the movement trend and seasonal changes in the U direction of the GNSS station. Therefore, the model can be applied to GNSS vertical time series modeling and prediction research.

Abstract:Aiming at the situation that the existing sorting algorithms were more or less dependent on prior information or difficult to adapt to multi-function radar, a multi-station fusion sorting algorithm based on set pair potential of partial coefficients was presented. The partial connection number parameter was introduced from the set pair analysis in the mathematical field to establish a clustering model. On this basis, the decision level fusion of clustering results was carried out by using the arrival time difference parameter in the multi-station cooperation mode. The actual measurement data and simulation results show that the algorithm can adapt to multi-functional radar systems such as search, acquisition and tracking,and realize the accurate clustering and fusion of radar pulse signals without any prior information. The sorting success rate is more than 97% in case of the jamming pulse ratio is lower than 60%.

Abstract:Aiming at the problem that the energy consumption of UAV(unmanned aerial vehicle) with high visual range and high maneuverability characteristics in the air ground efficient data communication system assisted by MEC(mobile edge computing) of UAV with high visual range and high mobility characteristics has a direct impact on the communication quality and multi-user and multi service requirements, a alternating iterative optimization method was proposed to minimize the system energy consumption on the premise of ensuring user experience. By establishing a UAV-MEC network system containing five sub models of UAV trajectory, channel model, local computing model, computing unloading model and UAV energy consumption, the UAV trajectory, user unloading volume and UAV power were jointly optimized. The system energy consumption was optimized. The simulation results show that compared with existing benchmark schemes, the computational energy consumption of end users reduce by 35%, and the overall performance of the system is improved.

Abstract:In practical applications, multiple types of array errors exist simultaneously. In view of the orientation dependence of array errors in this case, an improved MUSIC(multiple signal classification) algorithm based on MST(manifold separation technique) was proposed, which can effectively solve DOA(direction of arrival) estimation problem under the influence of multiple array errors. The sampling matrix, which contains all the non-ideal characteristics of the array was obtained by using MST, so as to achieve accurate direction finding. By using two-dimensional Fourier transform, the 2D spatial spectrum was solved. Compared with existing MUSIC algorithm, the computation amount of spectrum peak searching was reduced. Theoretical analysis and simulation verify the effectiveness of the algorithm, which can provide reference for the solution of practical problems.

Abstract:In order to improve the maneuverability and stability of underwater robots, a novel underwater robot driven by quadrotor and undulating fin was developed and its attitude control algorithm was proposed. The kinematics and dynamics model of cooperative propulsion by the propellers and the fin was established. The resistance coefficient was obtained by fluid numerical simulation. And the six-degree-of-freedom dynamic model of the robot was constructed. The attitude control strategy using hybrid drive of propellers and fin was proposed. A four degrees of freedom cascade proportional-integral-derivative controller and a control allocation algorithm were designed. The simulation model was established in MATLAB/Simulink software, in which pose curves in fixed depth cruise motion, heave motion and pivot steering motion were simulated and analysed. In addition, the influence of random interference on attitude control was simulated. Experimental results show that the robot has good attitude control performance. At the maximum undulating frequency, the attitude angle error of the prototype is less than ±4°; and the depth error is less than ±5 cm. The simulation and experimental results verify the feasibility of the novel underwater robot and the attitude control algorithm of propeller-fin cooperative propulsion.

Abstract:To optimize the design process of an autopilot and find the optimal design parameters, a new design method based on optimal control for a three-loop autopilot was proposed. It generates a three-loop autopilot topology by designing the cost function of the optimal control problem, and obtains multiple parameters of the three-loop autopilot by solving the optimal control problem. The impact of penalty weights in the cost function on the performance indicators of the autopilot was further studied and analyzed. Experimental results show that the three-loop autopilot designed by optimal control method has better performance compared with traditional design methods. And it also has good robustness against model-parameter uncertainties and unmodeled high-frequency dynamics of the system.

Abstract:A cooperative search method of multiple AUV (autonomous underwater vehicle) on the basis of improved BSO (brain storm optimization) algorithm was proposed to search underwater moving targets. The target motion was predicted on the basis of Markov process, both the detection information and prediction information were used to update the target existence probability. AUVs shared the target existence probability, environmental uncertainty, and the coordination of pheromones, then planed the search path by rolling optimization strategy. The effectiveness and robustness of the proposed method were verified by simulation. The simulation results show that the method can search moving targets under different motion patterns, the search effect is better than the random algorithm, traversal algorithm and BSO algorithm, it is not sensitive to different initial departure positions of AUVs, improving the flexibility of tactical use.

Abstract:In order to further expand the application range of lithium batteries, the high-rate pulse charging characteristics of lithium-ion batteries in different state of charge were studied based on the high-power energy recovery in electromagnetic launch scenarios. Based on the pseudo-two-dimensions electrochemical model, a high-rate pulse charging model of high-power lithium batteries was established by optimizing the diffusion coefficient. This model was used to analyze the variation of lithium deposition potential of lithium batteries charged by high-rate pulse with different state of charge. Through the cycling experiment and post-mortem analysis of lithium batteries, the aging behavior and aging mechanism of lithium batteries in different state of charge high-rate pulse charging were studied, and the aging mechanism is consistent with the simulation analysis results. The above research results can not only provide a reference for the application of lithium batteries in high-power energy recovery scenarios, but also provide a reference for the optimization of fast-charging lithium batteries.

Abstract:For the self-developed piezoelectric injector and actuator, a compensation control strategy based on voltage feedback was designed, a six-stage circuit driving mode was adopted, and the closed-loop compensation control of the driving voltage at both ends of the actuator inside the piezoelectric injector, charge and discharge process based on triangular waveform driving current were realized. It improved the utilization rate of circuit energy and reduced the peak current. At the same time, the drive circuit was tested. Test shows that the charging time is shortened by 0.06 ms, the discharge time is slightly shortened by 0.01 ms, the minimum pulse width for the actuator to reach the maximum displacement is shortened to 0.3 ms, and the peak current is reduced by 3 A, which verifies that the drive circuit has improved in response speed and safety.

Abstract:To study the application of UAVs (nmanned aerial vehicles) in area reconnaissance, a cooperation mode of truck-supported multi-UAV coverage reconnaissance and a collaborative path planning algorithm were proposed. With the goal of minimizing the task completion time, a mixed integer programming model was established considering the road constraints on the vehicle path and the energy constraints of the UAVs. A heuristic algorithm based on the idea of iterative relaxation was designed. In the test scene of 60 km²,16 target areas were randomly set. The proposed algorithm realizes the coverage path planning of the truck and the UAVs, and the total reconnaissance task time is 1.593 h, which verifies the feasibility of the vehicle supporting the multi-UAV mode and the effectiveness of the algorithm.