Volume 26,2025 Issue 2

• Contents

  Abstract:2025年26卷第2期目次

  Abstract (9) HTML (0) PDF (209.94 K) (5) Collect
Military Aviation
• An Analysis of Interaction on Tire-Wet Pavement under Aircraft Dynamic Load
  CAI Jing1;2; SHEN Zhe1; ZHOU Ning1; LI Yue1; FAN Yifei1

  Abstract:Based on the dynamic coupling simulation model of landing gear-tire-wet pavement in consideration of the influence of pavement flatness, the time history curves of tire wheel cardiac displacement at take-off and landing stages are obtained. On this basis, the finite element software is used to simulate and analyze the variation law of supporting force, contact area and displacement resistance of accumulated pavement under dynamic load at landing and takeoff stages, obtaining the dynamic load influence coefficient of critical hydroplaning speed under dynamic load. The results show that the pavement support force, contact area between tire and pavement, displacement resistance and critical hydroplaning speed are all lower than those under static load at take-off and landing stages. At take-off stage, the difference between pavement support force of dynamic and static load is small, the displacement resistance decreases by 0.3~3 kN compared with the static load, and the critical hydroplaning speed decreases within 5.5 km/h; At landing stage, the pavement support force is reduced by 5%~10% compared with the static load, and the corresponding displacement resistance is reduced to the maximum by 50%. The critical hydroplaning speed changes sharply, and the difference is between 5 and 9 km/h. Based on the above-mentioned change law of critical hydroplaning speed, the ratio of critical hydroplaning speed of dynamic and static load is defined as the influence coefficient of dynamic load, and the value of this coefficient is a range from 0.95 to 0.99 under different taxiing conditions; In view of the fact that the critical hydroplaning speed of the aircraft decreases greatly during the landing stage and the hydroplaning risk is higher, the dynamic load influence coefficient is taken as 0.96 for safety.

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• An Assessment of Capability for Mission in Aircraft Power Supply System Based on Probability Statistics and Expert Evaluation
  HU Chenyu1;2; PAN Jinxin1; FANG Xin3; JIAO Xiaoxuan1; JING Bo1

  Abstract:In view of the task capability evaluation in power supply system at an aircraft, a method based on statistical analysis and expert evaluation is proposed. Firstly, the power supply system at a certain type of aircraft is introduced, and its main failure modes and failure reasons are analyzed. Secondly, the Weibull distribution of power supply system faults is fitted through the statistical data from power supply system faults, and a method of calculating equipment fault probability during the task based on posterior knowledge is proposed to meet the requirements of equipment tasks. On this basis, according to the differences in the specific environment and intensity of task, the environmental factors in the power supply system are rated by using the method of expert experience scoring in comprehensive consideration of the vibration, load, natural environment and other factors. The results show that the proposed method can effectively predict the failure probability of the key components in the power supply system under the condition of fulfilling the mission, and comprehensively evaluate the mission environmental factors, supporting the decision of fulfilling the mission.

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• A Comprehensive Evaluation of Engine Nacelle Cooling and Ventilation Based on Limited Tolerance Relation
  ZHANG Hao

  Abstract:In order to expand the evaluation system of the power plant’s cooling and ventilation flight test, and quantitatively assess the comprehensive performance level of the cooling and ventilation system under conditions of missing temperature measurement data in the engine nacelle during flight tests, the concept of integrated nacelle temperature margin is introduced, and research on a comprehensive performance evaluation method for cooling and ventilation suitable for incomplete flight test data is made. The K-means clustering algorithm is utilized for making the discretization of nacelle temperature data, and determining the weight of nacelle temperature indicators in combination with the limited tolerance relation of rough set theory. A comprehensive performance evaluation method for cooling and ventilation of engine nacelle is established and the algorithm is applied to a three-engine helicopter. The factors to influence the comprehensive performance of the cooling and ventilation system are evaluated. The results show that the changes of technical state and the engine position have great influence on the integrated nacelle temperature margin, and the maximum difference reaches 65.5 ℃ and 83.2 ℃.The integrated nacelle temperature margin can characterize the comprehensive performance of cooling and ventilation. And this method is universal, and can be used as a supplement to the traditional evaluation method of cooling and ventilation flight tests.

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• Research on the Algorithm of Aircraft Fuel Quantity Based on RBF Neural Network
  LUO Yunhe; ZHAO Zheng

  Abstract:In view of the problems that the look-up table interpolation method used in aircraft fuel measurement is low in efficiency, low in accuracy, and is not good at the fault tolerance of the neural network applied to the calculation of aircraft fuel quantity, the fuel quantity algorithm based on RBF neural network is studied. By enhancing the discrete distribution of the fuel tank volume characteristic database to optimize the training samples, refining the neural network training algorithm to improve the fault tolerance for the input data, and employing genetic algorithm to optimize design parameters of the neural network, generalization capability and training efficiency of the RBF neural network in the fuel quantity calculation are effectively improved. According to the calculation example of an aircraft fuel tank and corresponding ground tests, the data dispersed method of tank models in this paper can further accurately describe their volume characteristic, with a 34.8% reduction in RMSE of interpolation calculation compared to the equidistant cutting method. The developed RBF neural network is good at the calculation accuracy, improving efficiency compared with the interpolation calculation method being about 5 times; Compared with the OLS algorithm, the improved algorithm has a 61.5% reduction in the estimated RMSE of test samples when the input parameters have errors, and the fault tolerance is significantly improved; The proposed method has a certain of practical value in engineering.

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Aerospace Defense
• A Large-Scale Target Threat Assessment Based on Improved Skyline Selection Methods
  LIU Xiangyu1; WANG Gang1; GUO Xiangke1;WANG Siyuan1;HE Sheng2

  Abstract:For large-scale complex combat scenarios, firstly, threat assessment method is studied to improve the selection of skyline method, and in designing a clustering method, a parameter adaptive density grid clustering method is proposed by the fuzzy theory to process large-scale targets, and facilitate the subsequent rapid threat assessment. Secondly, a multilevel skyline selection method is proposed, avoiding the complex process of traditional threat assessment methods such as the weight setting process, and avoiding the complex process of traditional threat assessment methods such as weight setting, and eliminating many interfering factors such as personal preference in the process of weight setting. Finally, a multi-indicator representation method of radar map is established, providing a basis for targeted decision-making by the commanders. The results of simulation and comparison experiments show that the subsequent target allocation and fire interception based on the threat assessment method ultimately achieve better combat effectiveness.

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• Performance Analysis of Direction of Arrival Estimation under Different Uniform Circular Arrays
  ZHOU Shuang1;2; ZHOU Li1

  Abstract:The uniform circular array being capable of two-dimensional direction of arrival (DOA) estimation, suitable for wideband scenarios, and easy to deploy, the widely application is made in civilian, military, and astronomical detection fields. In response to the need for two-dimensional high-resolution DOA estimation in the frequency range of 0.8 to 6 GHz, optimization design and comparative analysis of the DOA estimation performance of uniform circular array models based on the multiple signal classification (MUSIC) algorithm are conducted to determine the optimal array configuration. The structures of the non-centered circular array and the centered circular array models are introduced. The theoretical influence of circular array forms on direction-finding is derived. The simulation experiments are conducted by using the MUSIC algorithm. The DOA estimation accuracy of five array models, including non-centered 7-circular array, non-centered 8-circular array, non-centered 9-circular array, centered 8-circular array, centered 9-circular array, and centered 10-circular array, under different signal-to-noise ratios (SNR), sampling rates, and radius-to-wavelength ratios, is compared. A comprehensive analysis is conducted with performance indicators such as beamwidth, resolution, and others simultaneously. The results show that for high precision two-dimensional DOA estimation requirements in the 0.8 to 6 GHz frequency band, the centered 8-circular array achieves very good results in the direction-finding performance.

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• An Improved Fuzzy Comprehensive Evaluation Method for Effectiveness Evaluation of Military-Civilian Integrated Information and Communication Support
  CHEN Jun1;2; LI Jianhua2

  Abstract:According to the requirements of information-communication operations and the characteristics in military-civilian integrated information-communication system, an effectiveness evaluation method of military- civilian integrated information and communication support is proposed based on improved fuzzy comprehensive evaluation. Firstly, the key factors to affect the effectiveness of civil-military integrated information and communication support is analyzed by the analytic hierarchy process (AHP), and an evaluation index system is constructed by the improved Delphi method. Secondly, the weight of every layer index is calculated by 1-9 scale method, and the consistency is checked. And, based on the direct evaluation of quantitative indicators, the qualitative indicators are quantified by using fuzzy mathematics theory, thus obtaining the effectiveness evaluation calculation model, and improving the objectivity of the quantification of qualitative indicators. Finally, the effectiveness of the evaluation method is verified by a practical example, and the countermeasures and suggestions for improving the military civilian integration information and communication support system are given. This provides important reference for the optimization and efficiency improvement of military civilian integration information and communication systems.

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Electronic Information and Communication Navigation
• A Real-Time Image Semantic Segmentation Method Based on Dual Branch Fusion
  SONG Yuqin; LOU Hui; ZHANG Qi; SHANG Chunliang

  Abstract:Aimed at the problems that faulty classification and incomplete segmentation are in existence in segmenting multi-scale objects to the existing real-time semantic segmentation networks, a real-time semantic image segmentation method is proposed based on dual branch fusion. The method introduces a scale attention fusion module that is able to fuse object spatial feature and semantic information extracted from the detail branch and semantic branch, thereby improving the accuracy of the network for multi-scale object recognition. The edge loss function is used to guide the detail branch into learning the object edge contour, improving the network’s segmentation performance on object edge details. Finally, a global perception module is constructed to enhance the global context perception capability of the network. The experimental results demonstrate that the proposed method achieves the mean Intersection over union (mIoU) of 78.1% and 76.2% on the CityScapes and CamVid datasets respectively. Additionally, the mean pixel accuracy (mPA) is 87.6% and 85.4%, respectively. For small-scale object edges, there is a more accurate segmentation, coming up to the real-time requirements on a single GTX 1080Ti GPU, and frames per second (FPS) achieves 59.8 and 43.5 respectively.

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• A Design and Implementation in Ionospheric HF Wideband Communication System Based on SC-IFDMA
  WANG Yizhuo; ZHANG Yang; ZHANG Xiao; WANG Guanlin; YANG Yunchong; REN Peng

  Abstract:Aimed at the problems that in order to meet the needs of the over-the-horizon long range communication being reliable for aircraft in super-sight-distance on far oceans and far territories, and the timefrequency double-selective fade is severe in shortwave ionospheric reflection channels, a HF wideband communication system is proposed based on single-carrier frequency division multiple access (SC-IFDMA). The proposed method is to utilize a preamble detection algorithm in combination with segmented correlation and selective RAKE reception, ensuring both the missed detection and false alarm probabilities to reach 10-4 or lower under low signal-to-noise ratio (SNR) of -15 dB. The frequency offset estimation and SNR estimation are achieved by utilizing the repetitive structure of SC-IFDMA symbols in time domain, saving the system overhead and enhancing the transmission performance. Finally, the system prototype of the semi-physical test system is built based on USRP, and the loopback test of single link is completed in the channel simulator environment. The test results indicate that the system prototype can achieve reliable Aimed at the problems that in order to meet the needs of the over-the-horizon long range communication being reliable for aircraft in super-sight-distance on far oceans and far territories, and the timefrequency double-selective fade is severe in shortwave ionospheric reflection channels, a HF wideband communication system is proposed based on single-carrier frequency division multiple access (SC-IFDMA). The proposed method is to utilize a preamble detection algorithm in combination with segmented correlation and selective RAKE reception, ensuring both the missed detection and false alarm probabilities to reach 10-4 or lower under low signal-to-noise ratio (SNR) of -15 dB. The frequency offset estimation and SNR estimation are achieved by utilizing the repetitive structure of SC-IFDMA symbols in time domain, saving the system overhead and enhancing the transmission performance. Finally, the system prototype of the semi-physical test system is built based on USRP, and the loopback test of single link is completed in the channel simulator environment. The test results indicate that the system prototype can achieve reliable communication with an adaptive rate ranging from 200 to 20 000 bps and a bit error rate below 10-5 within the SNR range of -15 to 5 dB.

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• A Navigational Equipment Bearing Remaining Useful Life Prediction Based on Deep Learning
  DANG Huiying1;2;LI Hailin1;WU Beiping1;3;YU Jiayu1;4;ZHUANG Yinchuan5

  Abstract:As a crucial component of navigation equipment, bearings affect the positioning accuracy and safeguarding capability of the navigation equipment. In predicting the remaining useful life (RUL) of equipment, traditional machine learning algorithms are limited to dealing with the problems of complex nonlinear characteristic signals. For the above-mentioned reasons, a new prediction framework for RUL of bearing based on attention mechanism(AM) and bidirectional long short-term memory (Bi-LSTM) is proposed (Bi-LSTM-A). First, a one-dimensional convolution neural network (CNN) is added to the front of the structure to extract local features from the original signal sequence, and then, the signals are analyzed and predicted by combining bidirectional long short-term memory network with attention mechanism. finally, the predicted results are output through the fully connected layers at the end of the network. In comparison with the similar algorithms, the results show that the proposed method can accurately predict the equipment remaining useful life, and is good in predicting efficiency and accuracy.

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Unmanned Combat
• A Three-Dimensional Path Planning for Drone Based on Osprey Strategy Snake Optimizer
  CHEN Haiyang; WEN Shiqi; ZHANG Jiangqi; DU Wei

  Abstract:Aimed at the problems that search ability is inadequate in search, convergence is slow at speed, and susceptible to local optima in the intelligent optimization algorithm for solving the UAV 3D flight planning problem, an Osprey Strategy Snake Optimizer (OSSO) is proposed. Firstly, Bernoulli chaotic mapping is introduced to initialize the population, expand the individual search range, and enrich the diversity of the population; Secondly, the search strategy is improved in combination with the ideas of submerged predations, stochastic step and precise mining in the Osprey Strategy Snake Optimizer, and the global search capability is enhanced; And then, the dynamic opposition-based learning is utilized for updating population, balancing the algorithm’s global exploration and local mined ability, and improving the algorithm’s ability to deal with local optima. Finally, two 3D models are constructed by the function method and elevation data respectively, and the simulation experiment is performed by taking the length of trajectory, the distance in threat zone and the drone physical constraints as the judging indexes. The experimental results show that the OSSO algorithm is rugged, and good in stability and in effectiveness in solving the three-dimensional track planning problems.

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• A Prediction of Air Target Combat Intention Based on GRU
  LEI Lei1; TENG Fei2; QUAN Wen3; NI Peng4

  Abstract:In actual air combat, the target combat intention is realized by a series of tactical actions, and the target state is present to the characteristics of time sequence and dynamic change. The traditional operational intention recognition method only relies on a single moment of reasoning, which is not scientific and effective, and fails to predict the enemy’s intention in advance. Therefore, the bi-directional propagation mechanism and an attention mechanism are introduced on the basis of the gated recur-rent unit (GRU), and a method for predicting the combat intention of aerial targets is proposed. This method is to construct the air combat intention feature set through a layered method, encode to generate numerical time series features, and encapsulate domain expert knowledge and experience into labels. The BiGRU network is used for in-depth learning of air combat features, and the attention mechanism is used to adaptively assign feature weights to improve the accuracy of air target combat intention recognition. In order to realize the advance prediction of the target intention, the air combat feature prediction module is introduced before the intention recognition, and the mapping relationship between the predicted feature and the combat intention type is established. The simulation experiments show that the proposed model can predict the combat intention of the enemy’s air target by one sampling point in advance based on the accuracy of 89.7% intention recognition, and has obviously significance in improving the real-time performance of intention recognition.

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Airport Protection
• A Decision-Making Method of Minimum Operating Strip Based on Collision Detection
  ZHAO Hongduo1;2; XIA Chang1;2; GAO Dachen1;2; MA Lukuan1;2

  Abstract:At the scene of emergency rescue, how to determine minimum operating strip(MOS) is still a question after runway is being damaged, and this paper proposes a decision model based on collision detection between damage bounding circles and rectangles. This model helps quickly identify MOS, and establish an evaluation system with 11 indicators, including repair time, mission requirements, and safety. Using the fuzzy analytic hierarchy process(FAHP) and TOPSIS, optimal decisions are made for MOS selection. This model is applied to runway 2 at Al taqaddum airport to simulate debris distribution. This algorithm enables the generation of 250 potential minimum strip solutions, and the best one is selected based on the scenario and mission conditions. This approach demonstrates that the model is suitable for determining the minimum strip post-runway damage.

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• A Study of Mechanical Properties and Frost Resistance of High-Performance Concrete Repair Materials Doped with Carbon Nano-Fiber
  LI Changhui; XUE Wenchao; QI Lin; LIU Lingzhi; WANG Daotong

  Abstract:This article introduces a repair material being characteristic of high-performance concrete doped with vapor grown carbon nano-fiber reinforcement (VGCF) and carbon nano-tubes (CNT) for runway. That material of adding nano-fibers to concrete can improve its mechanical properties and endurance is a well-known fact. However, the uneven distribution of nano-fibers in the cement matrix can lead to a decrease in performance. The article focuses on the adaptability of repair materials and cement-based pavement materials, and analyzes the influence of carbon nano-fiber materials on the micro mechanism of con crete reinforcement. Mix proportion tests are conducted by doping carbon nano-fibers with different mass fractions in concrete, and the compressive strength, bonding strength, mass loss rate under freeze-thaw cycles, and bonding strength loss rate are measured respectively. The research shows that when the CNT104 content is 0.1%, the compressive strength and bonding strength of concrete are 60.6 MPa and 11.3 MPa respectively, and the 150 freeze-thaw cycles being over, the mass loss is minimum. When the content of CNT107 is 0.15%, the compressive strength and bonding strength are fairly good, i.e. 59.1 MPa and 11.5 MPa respectively. When the content reaches 0.2%, the mass loss is minimal after 150 freeze-thaw cycles. When the VGCF content is 0.15%, the concrete reaches its maximum compressive strength and bonding strength, i.e. 68.0 MPa and 18.6 MPa respectively. At the same time, the concrete with different contents of VGCF shows better frost resistance. At a content of 0.15%, the quality loss rate of concrete after freeze-thaw cycles is the lowest. After 150 freeze-thaw cycles, the bond strength is measured again. By comparing before and after freeze-thaw, it is found that the decrease rate of bond strength with 0.15% VGCF added is 32.79%, which is the lowest among all groups. The results indicate that taking UHPC mixed with 0.15% VGCF as runway repair material, its fairly good adaptability to cement-based pavement materials is very protruding.

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