Volume 27,2026 Issue 2

• Contents

  Abstract:2026年27卷第2期目次

  Abstract (83) HTML (0) PDF (227.17 K) (34) Collect
Military Aviation
• A Flight Conflict Detection Method of Integrating Spatial Geometric Modeling and Machine Learning Based on LightGBM Algorithm
  ZHANG Libiao1;2;WEN Xiangxi1;WU Minggong1;LIANG Liang2;LI Jiawei3;PENG Chuan4;SU Rui1

  Abstract:Aimed at the problems that timeliness is poor in geometric flight conflict detection methods and detection samples are imbalanced in machine learning-based detection methods, this paper proposes a flight conflict detection method of integrating spatial geometric modeling and machine learning. Firstly, in combination of synthetic multi-dimensional features such as aircraft position and velocity, the geometric method is used to determine conflicts based on the velocity obstacle method and the three-dimensional cylindrical protection zone. In order to address the poor timeliness of geometric judgment, a machine learning method is introduced. Conflict samples being short and training samples being imbalanced, the lightweight Gradient Boosting Machine (LightGBM) algorithm with a class weight adjustment mechanism is selected. Finally, the proposed method is verified by using actual secondary radar data collected in the Xi’an area. The experimental results show that the operating speed by the proposed method is 3.91 times faster than that by the geometric method. Compared with typical algorithms such as Random Forest (RF) and K-Nearest Neighbors (KNN), the proposed method in conflict judgment is an accuracy increase of 19% and 91% respectively.

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• A Method of Planning Arrival/Departure Fixesin Military Multi-Airport Terminal Airspace Based on Improved Particle Swarm Optimization
  CHEN Wei;YU Fuping;SHEN Di;PENG Yating

  Abstract:Aiming at the problem of insufficient dynamic adaptability of existing methods to the terminal airspace of multiple military airports,through a comparison of opertational differences between military and civil aviation,this paper proposes redundancy design and dynamic adjustment mechanisms to constitute a multi-objective optimization model with dual goals, i.e.traffic flow balancing and minimization of total flight path length through making a comparison between military and civil aviation operations.On the basis of the traditional Particle Swarm Optimization (PSO) algorithm, this paper designs an improved Multi-Objective Particle Swarm Optimization algorithm (MOPSO) by integrating the local optimization mechanism of Simulated Annealing (SA), the non-dominated sorting strategy of NSGA-II, and initialization using Logistic chaotic mapping.Furthermore, the entropy weight-TOPSIS method is employed to conduct a comprehensive evaluation and selection of the solution set, ultimately determining the optimal arrival and departure fixes planning scheme.The results show that compared with the conventional Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, this proposed improved algorithm achieves an average improvement of 23% approximately in the Hypervolume metric, and the Inverted Generational Distance metric and the Spacing metric decrease by approximately 45% and 39%respectively.This method can effectively balance the contradiction between traffic balance and flight path optimization, providing a scientific basis for the efficient planning of military aviation terminal airspace in multi-airport areas.

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• An Inductance Calculation Method Based on Equivalent Motor Models
  LIU Xin1;2;HAN Yao1

  Abstract:In view of the spatial electromagnetic structure of variable-cross-section helical stator in toroidal motor, this paper proposes an inductance calculation method based on equivalent motor models. Firstly, the spatial helical currents in worm inner stator are analyzed to obtain effective current components, and then, equivalent motor models are established for the planet rotor during its revolution and rotation, and the relationship between its revolutionary and rotational electrical angles is derived. The inductance of helical windings in inner stator is derived by the double-reaction theory, revealing the periodic variation pattern of inductance with respect to the position of the planet rotor as well as the validity of the inductance. Through voltage and torque equations of toroidal motor, voltage limit ellipse, electromagnetic torque variation pattern, and the maximum torque per ampere trajectory are obtained. The results show that the voltage limit ellipse presents a class elliptical shape under the influence of quadrature-axis magnetic circuit saturation effect, and the electromagnetic torque fluctuates periodically with the revolutionary electrical angle of planet rotor. Finally, the influence of electromagnetic parameters of toroidal motor on the electromagnetic torque is analyzed. This lays a foundation for the optimization of torque control strategies and the promotion of engineering applications of this motor.

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• A Study of Helicon Wave Plasma Source Discharge Based on Langmuir Probe Diagnostics
  DUAN Pengzhen1;SU Xiaolu1;XIE Ping1;LI Yiwen2

  Abstract:Aimed at the problems that discharge mechanisms are complex and discharge characteristics of helicon wave plasma sources are unclear, this paper systematically investigates the discharge characteristics of working gases such as argon,helium,and nitrogen,as well as the effects of magnetic field strength,RF power,and gas pressure on argon discharge properties by the RF-compensated Langmuir probe diagnostic method. The experimental results indicate that argon exhibits optimal performance in terms of discharge intensity and ion density,making it more suitable for electric propulsion systems.A magnetic field is necessary for the transition from inductive discharge to wave-coupled mode.Under condition of specific parameters (0.40 Pa,200 G),there undergoes a H-W mode transition 600 W around in the process of argon discharge, with ion density reaching the order of 1018 m-3 in the wave mode. Although appropriately increasing the discharge gas pressure can enhance power coupling efficiency and discharge intensity,yet when thepressure exceeds a certain level,the increase in ion density slows down or even saturates. The conclusions demonstrate that the mode transition in helicon discharge is closely related to external parameters,and this study provides experimental evidence for elucidating its physical mechanisms and propulsion applications.

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Electronic Information and Communication Navigation
• A Design of Single-Fed Metal Mesh Circularly Polarized Antenna Turned in the Direction of Satellite Applications
  YANG Wendong;SUN Haiyang;ZHANG Xiaoyuan;ZHAO Xun

  Abstract:A metal mesh circularly polarized antenna whose cost is low,manufacture is easy,and property is a material of environmental friendly protection compared to the traditional processes and the transparent material,is designed based on screen-printed copper paste.The antenna can be integrated into solar panels used on CubeSats or other micro-satellites.Its structure is intent to improve the axial ratio bandwidth relative to single-fed circular polarization,and simultaneously,to simplify the complex antenna structure compared to the dual-fed circular polarization.Circular polarization characteristics are achieved by adopting a ring with a gradual line width,a mesh feedline,and taking a ground plane as the antenna patch through asymmetric ground planes and a special feeding method.The simulation and measurement results show that the proposed antenna can obtain an effective signal radiation in the C-band (4~8 GHz),and its impedance bandwidth can reach 68.3% (5.5~11.2 GHz),and an axial ratio bandwidth can reach 25.1% (5.44 ~7 GHz).While maintaining a sufficient axial ratio beamwidth,a peak gain of 4.86 dBic is realized,fully meeting the requirements of satellite-to-earth communication applications.

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• Research on Construction Method of 3D Geomagnetic Reference Map Based on U-Net Neural Network
  HAO Aowei1;HU Jing2;3;JI Xiaolin1;YANG Binfeng1;GUO Jiaojiao1;LIU Jiazheng1;YE Decheng4

  Abstract:The downward continuation algorithm of geomagnetic potential field is a typical ill-posed problem in mathematics. Aimed at the problems that the traditional downward continuation of geomagnetic data is susceptible to the effects of noise and continuation distance, this paper explores the downward continuation of magnetic anomalies by using the U-Net neural network. Magnetic anomalies obtained at different heightsvia forward modeling of simple prisms and complex combined prisms, are taken to be labels of machine learning with 5 000 label groups being constructed for each dataset. The dataset is divided into training, test, and validation sets at a ratio of 8∶1∶1. The construction of machine learning labels is in comprehensive consideration information such as geometric position of the model center, the length, width, and height of the model, as well as magnetic inclination, magnetic declination, and magnetization intensity. Under condition of interference-free experiments, the average relative prediction accuracy is 97.0% for the single prism model and 95.2% for the three-combined prism model. Under the interference of 5% Gaussian noise, the average relative prediction accuracy of the combined model remains 94.9%, showing excellent anti-interference performance. And simultaneously, the model exhibits strong distance robustness within the range of continuation distances involved in the experiments. This study verifies that the UNet network can effectively realize downward continuation and has broad application prospects in the construction of 3D magnetic reference maps.

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Unmanned Combat
• A Method of Controlling Multi-Agent System Low-Oscillation Collision-Free Flocking Based on High-Order Artificial Potential Field
  WAN Lujun1;2;LI Qiang1;XIAO Boyi1;TIAN Jiwei1; ZHONG Yun3

  Abstract:Multi-agent system flocking control has been a research hot topic in recent years.In view of the problems that there remain oscillation and slow initial response in second-order flocking control systems, this paper proposes a flocking control algorithm incorporated higher-order artificial potential fields by integrating the general properties of artificial potential fields required for multi-agent systems.Viewing the potential field gradient as the deviation of the agent's expected position, the control law is designed from the perspective of trajectory tracking. And, the Hessian matrix of the artificial potential field is introduced into the flocking control, and an energy-based Lyapunov function is designed to prove out the stability of the flocking control method and the obstacle avoidance during the operation of the multi-agent system separately.Thenumerical simulation results show that the proposed high-order potential field method achieves a significant increase in the response speed of multi-agent flocking control, effectively suppressing the system oscillations.

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• A Path Planning for Multi Drones without Conflict Based on PF-CA* Algorithm
  YANG Jiale;WU Yarong;ZHAO Guhao;ZHOU Zhichong;WEI Xiaolong;ZHANG Lei

  Abstract:In response to the urgent needs of safe operation and collision avoidance for high-density drones in the context of low-altitude economy,this paper proposes a fast path planning algorithm without conflict for multiple drones based on the fusion of prime factorization and Cooperative A* (Prime-Factor-based Cooperative A* ,PF-CA* ).The algorithm is to integrate prime factorization with Hadamard product operations to achieve millisecond-level conflict detection among drones amid flight,and design a local path planning method based on altitude adjustment.Moreover,the reservation table mechanism of the CA* algorithm is improved.On the basis of ensuring the optimality of the initial pre-flight path,the overlap degree of the initial paths of multiple drones is reduced.A third-order Bezier smooth curve library is designed.In combination of the action characteristics of the pre-takeoff planned path,turning points are identified,and efficient smoothing processing of the path is realized.The simulation results show that the path planning without conflict based on this method is characterized by optimal path planning,low overlap degree,and high real-time performance.Within a 5 km × 5 km airspace,the single-cluster operation success rate of hundreds of drones is over 90%.This method can provide a solution to the path planning problem of multiple drones in complex urban low-altitude airspace.

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Ordnance Engineering
• A Design and Optimization of Electromagnetic Launcher with a Three-Stage Tilted-Pole Sextupole Field
  HAN Lei1;LIU Shaowei1;XIONG Ling2

  Abstract:Aimed at the problems that inter-stage magnetic coupling is weak and rotational torque generation is inefficient in conventional multipole electromagnetic launcher, this paper proposes a Three-Stage Tilted-Pole Sextupole Field Electromagnetic Launcher (3S-TP-SFEL).The parallelogram-section driving coils are used to enhance magnetic field uniformity and dynamically align projectile eddy current paths with magnetic field gradients.Based on Maxwell finite-element,electromagnetic characteristics and dynamic responses are comparatively analyzed by field-circuit coupling methodology between the proposed and conventional configurations.The results demonstrate that the tilted-pole topology optimizes axial-circumference magnetic field interactions, increasing armature rotational speed from 2 125 r/min to 3 000 r/min. Through identifying optimal operational parameters,being at a trigger position of 35 mm and at a torsion angle of 17°,a peak axial velocity reaches 203.26 m/s and rotational speed 16 738.02 r/min.The tilted-pole structure is valid in enhancing multistage magnetic synergy.

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Military Intelligence
• An Action Recognition Method Based on Attention Mechanism Using GCN-Bi-LSTM Network
  DUAN Rong1;LI Yuan1;LIU Qi2

  Abstract:In response to the challenges posed by existing action recognition methods that rely on skeleton information,particularly their low utilization of skeletal sequence data and difficulties in accurate recognition, this paper presents a novel action recognition approach utilizing a graph convolutional bidirectional long short-term memory (GCN-Bi-LSTM) network enhanced by an attention mechanism.Firstly,a nonphysical dependency relationship is constructed by leveraging the relative distances between skeleton nodes to enrich skeletal features.Secondly,a spatio-temporal graph convolutional network is employed to extract features from each video frame,thereby obtaining more sophisticated semantic representations.Finally, these frame-specific features are fed into the bidirectional LSTM network augmented with an attention mechanism to capture global temporal characteristics and then action discrimination capabilities can be enhanced effectively.Experimental results show that the proposed method can significantly improve recognition accuracy and has great potential for application in tactical action analysis and training scenarios.

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• A Beyond Visual Range Air Combat Situation Assessment Based on D-S Evidence Theory
  HUANG Xunan1; ZHANG Qiang2; ZHANG Tao1; LÜ Yan1; ZHAO Yu1

  Abstract:In view of the problems that traditional method is single and limited in Beyond-Visual-Range (BVR) air combat situation assessment, this paper introduces a multi-source information fusion evaluation framework based on D-S evidence theory. Taking assessment outputs of three distinct methods as independent evidence bodies and subsequently processing through D-S evidence theory for deep-level fusion, a comprehensive estimation of air combat situations is obtained. The fused evaluation results show that the characterization capability of key features for air combat situations is obviously enhanced compared to the individual methods. The fusion approach establishes a more rational and robust quantitative foundation for command decision-making in air combat operations, effectively contributing to the improvement of both scientific rigor and timeliness in air combat decision-making processes.

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• An Emergency Positioning Method Using Visual Matching Technology for Sparse Scenarios
  HU Jun1;WANG Wei1;ZHANG Xiya2;QU Jue1;WANG Qingli

  Abstract:Being aimed at the problems that satellite navigation is vulnerable to interference,inertial navigation relies on control points,and traditional intersection measurement methods are inefficient and are difficult to meet the emergency needs,simultaneously,traditional visual matching methods are deeply affected by illumination and viewing angles,and robustness is poor at feature-sparse scenes of deep mountains and gobi deserts,this paper proposes an emergency positioning method suitable for featuresparse scenes.First,the method is to extract ridge contours by a semantic segmentation model,and perform preprocessing including edge extraction and feature point down-sampling to solve the problem ofinsufficient discriminative information in feature-sparse scenes.And then,image matching is converted into feature point matching.In combination of in-vehicle motion constraints with long-distance imaging constraints,a descriptor integrating“local + global”spatial contexts is constructed to achieve rotation-invariant properties.At the same time,stable anchor points are introduced to build a global descriptor,and matching ambiguities caused by locally similar structures are mitigated through relative displacement vectors.Finally,based on polar geometry,the fundamental matrix and essential matrix are solved.In combination of the Perspective-n-Point (PnP) algorithm with triangulation and bundle adjustment (BA),the camera pose is optimized to derive geodetic coordinates.The experiments in feature-sparse scenes such as the Qinling Mountains and Zhouwan Town,Dingbian County demonstrate that the average positioning accuracy reaches 2.5~2.8 meters by the method,surpassing classical methods by 2~3 meters.Thoughcomputation time is moderately longer than that of the other classical methods,the method still maintains real-time capability (second-level response).The measurement efficiency is higher than that of the traditional intersection.This method achieves an optimal accuracy-efficiency balance for highway emergency positioning in mid-to-long-range ridge-dominated scenes without severe perspective rotation,exhibiting substantial engineering applicability.

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• A New Model of Translating SAR into Optical Images Based on Diffusion Schrödinger Bridge
  YUN Xiangya1;2;DONG Enzhi1;ZUO Xiaotong1;ZHAO Yuefei1;WANG Changlong1

  Abstract:In view of the problem that effective interpretation of SAR images is extremely difficult,this paper proposes a new model of translating SAR into optical images.The model is very unlike the existing methods relying on strictly aligned datasets for training, and does not depend on such preconditions,enabling the generation of images to assist in the interpretation tasks associated with SAR imagery. And the proposed method is to utilize the diffusion Schröinger bridge theory for decomposing the complex transformation relationships between SAR and optical images into multi-step generative processes. Through mitigating the impact of coherent spot noise(CSN)on feature extraction,an AD-DPM denoising preprocessing module is incorporated into the model. Furthermore,a ViT-UNet generator is employed for deep feature extraction,while incorporating PatchNCE regularization terms into the loss function to enhance the preservation of underlying structural components during the generation process.The experiments conducted by using the SEN1-2 dataset demonstrate that the proposed method can effectively convert SAR images into high-quality optical images that align with visual perception standards.Compared to the baseline method CUT,the PSNR、SSIM、FID and LPIPS metrics improved by 38.4%、42.2%、30.6% and 21.0%,respectively. These results provide a valuable reference for improving the efficient and accurate interpretation of SAR images.

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Basic Research
• Investigation on Ultra-Wide Temperature Stability of 0.8Pb[(Fe2/3W1/3)1-xTix]O3-0.2BiFeO3 Solid Solution Ceramics
  LI Haijuan;SHI Zhuoying;LIU Qiang;ZHANG Qian

  Abstract:As the application demands for electronic devices in extreme environments escalate steadily, multilayer ceramic capacitors (MLCCs) are imperative to withstand highly arduous operational conditions, including those encountered in desert oil exploration,hybrid electric vehicles,aerospace systems,and specialized military robotics.In this context,the development of dielectric ceramic materials characterized by a broad operational temperature spectrum,low sintering temperature,and superior dielectric performance has emerged as a pivotal challenge in driving the technological advancement of MLCCs.The 0.8Pb[(Fe2/3W1/3)1-xTix ]O3-0.2BiFeO3(x = 0,0.005,0.01,and 0.02) ceramics are synthesized using the solid-state reaction technique.Dense ceramic samples with pure perovskite structure are successfully obtained after sintering at a very low sintering temperature of 850 ℃.As x increases from 0 to 0.02,the room temperature dielectric permittivity (ε') increases slightly while the loss tangent (tan δ) decreases at 1 kHz,indicating the beneficial effects on the dielectric performance by Ti4+ doping.All samples maintain ΔC/C25℃ ≤±15% down to very low temperature.The composition with x=0.005 shows the widest temperature stability range of -130 ℃ to +85 ℃ at 1 kHz,and the dielectric loss is lower than 1% at room temperature,which well reaches the standard of the EIA X5R.This ceramic material with excellent temperature stability at ultra-low temperatures and an ultra-wide temperature range can not only match the cheap alloy Ag/Pd (where Ag≥70%) as the internal electrode to fabricate multilayer ceramic capacitors,which can greatly reduce the cost of ceramic capacitors,but also meet the requirements of a wider working temperature range and adapt to the changes of different environments.

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