Modern Defense Technology

Trajectory Planning for UAV Swarm Target Strikes in Urban Environments

Chen FEI, Liang ZHAO, Yongliang HE, Yincheng LI, Song XU

2025, 53(1): 1-10. doi:10.3969/j.issn.1009-086x.2025.01.001

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To solve the problem of UAV target strikes in complex urban environments， a UAV target strike method based on the electric eel foraging optimization （EEFO） algorithm is proposed. First， the method sets up two scenarios， namely the sparse environment without enemy defense and the dense environment with enemy defense， and designs corresponding constraint conditions and trajectory optimization cost functions to meet the flight needs in urban environments. Then， the EEFO algorithm is used to plan a reasonable target strike trajectory for the UAV. Finally， the flight trajectory and fitness value of the EEFO algorithm are obtained and compared with those of the other five algorithms： SO， SCA， WOA， MFO， and HHO. The experimental results show that in a sparse environment with enemy defense， the EEFO algorithm has higher trajectory planning efficiency and stability than the other five algorithms. It consumes the smallest trajectory cost and converges faster. In the dense environment with enemy defense， the EEFO algorithm has the optimal planned target strike trajectory and a better convergence trend of the consumed trajectory cost compared to the other five algorithms， with the highest task completion degree and better performance.

A Phase Transition Control Method for UAV Swarm Based on Birds’ Behaviors

Haonan QIU, Ming HE, Wei HAN, Xin XU, Haotian CHEN, Yiran WEI

2025, 53(1): 11-22. doi:10.3969/j.issn.1009-086x.2025.01.002

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UAV swarm has emerged as a crucial new combat force in information warfare. To tackle the challenges of collective shape control in UAV swarms driven by multiple tasks， a phase transition control method for UAV swarms inspired by birds’ behavior is proposed. Firstly， the behavioral patterns of bird flocks are analyzed， and the characteristics of collective defense behavior in bird flocks exemplified by sparrows are summarized. Then， a phase transition control model for UAV swarms based on four rules （four-rules phase transition model， FRPT） is built by introducing centripetal/centrifugal dual force and establishing “mutation” interaction rules. Next， with control parameters and order parameters defined and key control parameters regulated， the phase transition control of UAV swarm is achieved and the effectiveness of the proposed method is experimentally proved. Finally， through the optimal parameter solving of swarm intelligence optimization algorithms， the formation period of ordered phases is shortened by nearly 70%， which validates the optimization feasibility of the proposed method.The method is anticipated to be extensively applied in tasks such as reconnaissance and emergency rescue missions for UAV swarm perception.

Multi-target Tracking Algorithm Based on Information Association and Weighting

Yongzheng YU, Wei WANG, Zhiwei PU

2025, 53(1): 23-36. doi:10.3969/j.issn.1009-086x.2025.01.003

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A probability hypothesis density filtering algorithm based on information association weighting is proposed to address the two issues of decreased accuracy in multi-target state estimation and overestimation of the number of multi-targets， which are caused by asynchronicity and high-density clutter aliasing in passive and active radar detection information across multiple platforms. Firstly， a multi-target tracking model is constructed， and the mechanism of why existing algorithms are susceptible to clutter is analyzed. Secondly， a multi-target tracking algorithm based on information association weighting is derived. The tolerance time parameter is set according to the target speed and tolerable error， and the detection information with a short asynchronous time is approximated as synchronous information. The association algorithm is used to select passive and active radar information from the same target， and the minimum variance weighted fusion is used to improve detection accuracy. The randomly distributed clutter is filtered out， due to its association difficulties caused by large differences in angle values. Finally， simulation analysis shows that the proposed algorithm improves the accuracy of multi-target state estimation and reduces the overestimation of the number of multi-targets compared to existing algorithms.

Research Progress and Trend on Precision Airdrop System

Tao JIANG, Hang LU, Deyu TIAN

2025, 53(1): 37-44. doi:10.3969/j.issn.1009-086x.2025.01.004

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The development of precision airdrop systems has fundamentally transformed military supply by optimizing the timing， location， and quantity of supplies. This advancement has significantly enhanced the deployment and support capacities of troops at both the strategic and tactical levels. By analyzing different types of precision airdrop systems， the research status and key technologies of these systems， both domestically and internationally， are summarized. In addition， the emerging research trends in the key technologies that impact the supply capabilities of precision airdrop systems are discussed.

An Air Defense Deployment Method Based on NSGAⅡ Algorithm

Chenchen HUANG, Suhang LI, Zilong GAO, Yuebing CHENG, Zining Zhao

2025, 53(1): 45-51. doi:10.3969/j.issn.1009-086x.2025.01.005

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Traditional air defense weapon deployment methods primarily focus on optimization models under predefined scenarios， which are inadequate for adapting to the multi-level， multi-path airstrike modes encountered in actual combat. A multi-objective optimization algorithm based on NSGA-II is proposed for a defense system consisting of multiple targets and various air defense weapons. The covering capability and penetration probability are defined as two objective functions， with constraints including battle formation and terrain. This algorithm effectively evaluates the strengths and weaknesses of regional air defense deployments， and addresses the problem of optimizing air defense weapons placement under specific conditions. The simulation results demonstrate that the proposed method enhances cover capability and improves the interception effectiveness in specific air situations.

Semi-supervised Air Targets Combat Intention Recognition Based on Metric Learning

Chenhao ZHANG, Yan ZHOU, Futai LIANG, Tong ZHOU, Zihao SONG, Kai YUAN

2025, 53(1): 52-62. doi:10.3969/j.issn.1009-086x.2025.01.006

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The air battlefield situation provides a general description of the actions and states of all participants， while target combat intention recognition serves as a critical foundation for air battlefield posture assessment. To address the challenge of acquiring a large amount of labeled air target battlefield data amidst intense confrontation and rapidly evolving scenarios， a semi-supervised air targets combat intention recognition model is proposed based on metric learning. The model offers a method for uncovering potential patterns from unlabeled samples， thus reducing the reliance on extensive labeled data. In this model， the target time-series data encoder reduces the dimensionality of target data and produces an embedded representation. Based on this， loss values are calculated by measuring the similarity between labeled target sequences and intention types， as well as between labeled and unlabeled target sequences. The experimental results demonstrate that the model achieves combat intention recognition accuracy rates of 86%， 89%， and 91% with labeled sample rates of 30%， 40%， and 50%， respectively.

Evaluation of Combat Effectiveness of Anti-UAV Swarm System Based on Improved TOPSIS Method

Runze WU, Weishi PENG, Yixuan MA

2025, 53(1): 63-72. doi:10.3969/j.issn.1009-086x.2025.01.007

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Unmanned aerial vehicle （UAV） swarm tactics have emerged in recent years as a new approach to both attack and defense， capable of altering the course of warfare. However， limited research exists on evaluating the operational effectiveness of anti-UAV swarm systems， and commonly used evaluation methods have significant limitations. To address this， a method is proposed for evaluating the combat effectiveness of anti-UAV swarm systems by combining fuzzy analytic hierarchy process （FAHP） and criteria importance through intercriteria correlation （CRITIC） methods to determine weightings， followed by the application of an improved TOPSIS method. First， an evaluation index system for the combat effectiveness of anti-UAV swarm systems is developed using the OODA loop （observe， orient， decide， act）， a decision-making framework. Second， the FAHP-CRITIC method calculates the weightings of the evaluation indices. Third， the improved TOPSIS method is used to rank and optimize the effectiveness values of different schemes. Finally， the proposed evaluation method’s correctness and rationality are validated using control experimental data. A more scientific approach for evaluating the combat effectiveness of anti-UAV swarm systems is provided.

Design of Preset Performance Saturation Controller for Missile Formation with Error Constraint

Xianfeng WU, Baowen CHEN, Jingguang SUN

2025, 53(1): 73-80. doi:10.3969/j.issn.1009-086x.2025.01.008

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This paper studies the missile formation control problem under external interference， input limitations， and tracking error performance constraints. Based on communication topology theory， a missile formation model is established using the absolute error of each missile and the relative error of neighboring missiles. A missile formation model with an input-limited tracking error constraint is then presented using an error conversion function. An adaptive saturation formation preset performance controller is designed using the backstepping method， adaptive techniques， and an auxiliary system. The stability of the proposed formation controller is proved using the Lyapunov theory， which shows that the system’s tracking error can converge to the predetermined boundary range. The effectiveness of the controller is verified through digital simulations.

Research on Anti-missile Fire Control Technology of Key Anti-aircraft Guns Based on Target Angular Rate

Baobao WANG, Bin XIN, Shuaishuai WAN

2025, 53(1): 81-87. doi:10.3969/j.issn.1009-086x.2025.01.009

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To address the issue that traditional anti-missile fire control systems for key anti-aircraft guns lack sufficient response time when engaging supersonic and low-altitude penetration targets， this paper systematically investigates anti-missile fire control technology based on target angular rate. It proposes a fast hit solution based on the least squares preprocessing conversion measurement Kalman filter smoothing algorithm （LS-CMKFS） and an emergency hit solution based on angular rate. In addition， a fast calculation control strategy is developed， balancing the fire control system’s response time with computational accuracy. The simulation results confirm the effectiveness of this fire control algorithm in enhancing the interception performance of the anti-aircraft gun system.

Risk Assessment of Network Defense System Using Combination Weighting Based on Game Theory

Hang HU, Pengcheng LIU, Yuchen ZHANG, Mei WANG

2025, 53(1): 88-96. doi:10.3969/j.issn.1009-086x.2025.01.010

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A network defense system must balance both security and stability. To enhance its risk control capabilities， a comprehensive risk assessment model for the network defense system based on the combination of game theory and weight assignment is proposed. The risk evaluation index system is established through literature analysis， expert surveys， and factor analysis. The subjective and objective weights of the evaluation indices are calculated using the continuous ordered weighted average （COWA） and the entropy weight method （EWM）. The optimal combination weights are determined using game theory， and the risk evaluation level of the network defense system is assessed using the fuzzy matter-element method. A case study of a local area network （LAN） project validates the model. The results demonstrate that the model is a useful reference for assessing the risk of network defense systems.

Research of Hard and Soft Killing Weapon Target Assignment Based on Hybrid Particle Swarm Optimization

Shihao LIU, Xiaozhou CUI, Feifei WANG, Xiaofei HUANG, Cong WANG

2025, 53(1): 97-107. doi:10.3969/j.issn.1009-086x.2025.01.011

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In the soft hard collaborative combat mode of the air defense system， it is of great significance to reasonably and efficiently allocate targets for the coordinated interception of soft and hard killing equipment. This paper proposes a method for allocating targets for hard and soft killing weapon target assignment based on hybrid particle swarm optimization. The optimization indicators corresponding to the soft hard collaborative interception problem are analyzed. The comprehensive interception efficiency index of the target is integrated by using the shooting advantage of hard killing equipment and the interference advantage indicators such as suppression， frequency， and angle of soft killing equipment. The advantages of traditional particle swarm algorithm and genetic algorithm are combined， and an improved hybrid particle swarm algorithm is adopted. A coding structure suitable for simultaneous allocation of soft and hard equipment and a particle generation guidance operation that accelerates algorithm convergence are designed. The simulation results show that in the field fixed position air defense scenario， the hybrid particle swarm algorithm can quickly obtain the optimal target allocation scheme. Compared with traditional algorithms， the comprehensive interception efficiency of targets is significantly improved， and it has certain engineering application value in air defense command and control systems.

Node Importance Evaluation of Dynamic Reconfiguration System Based on Unit Attribute

Yukai PAN, Wenhao YU, Zhen TANG, Jiayi YIN, Wen ZHANG, Guoxu FENG, Yujie GUO

2025, 53(1): 108-119. doi:10.3969/j.issn.1009-086x.2025.01.012

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In modern combat， nodes differ significantly from the single-function nodes of the past， evolving towards multi-function integration. To address issues such as the characterization of node function diversity， the dynamic reconfiguration of system models， and realistic simulation of enemy network analysis in current node importance evaluations of combat systems， a dynamic reconfiguration model based on unit attributes for the enemy’s network is proposed. The concept of tactical weight is introduced， and multi-function integration of nodes and edges is achieved through attribute induction and attribute assignment. A method and algorithm for calculating the dynamic reconfiguration of network effectiveness are presented. Taking into account the actual operational context and efficiency， the node attack cost is incorporated， and a node importance evaluation model based on the contribution rate to system network effectiveness is proposed. In simulation experiments， node importance is evaluated using seven different metrics， including node effectiveness index， degree centrality， and betweenness centrality， under various spatiotemporal conditions. The decline in network effectiveness after network strikes is also analyzed. The simulation results demonstrate that the proposed method enables dynamic reconfiguration of the network post-attack， reflecting the network’s strong robustness and confirming the validity of the proposed algorithm.

A Method of Working Mode Recognition for Multi-function Radar Based on RGCN

Chunlai YU, Mingyue FENG, Hongbin JIN, Fuqun ZHANG, Qiangfei ZHANG

2025, 53(1): 120-128. doi:10.3969/j.issn.1009-086x.2025.01.013

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Multi-function radar has gained widespread application due to its flexible working modes， agile waveform characteristics， and ability to perform multiple tasks in parallel. However， these capabilities also pose significant challenges to radar intelligence reconnaissance and countermeasures. Recognizing the working modes of multi-function radar serves as a fundamental step for subsequent threat assessment， adaptive countermeasures， and guided attacks， directly influencing the specificity and effectiveness of radar countermeasures. In this paper， a novel method for recognizing the working modes of multi-function radar， leveraging relational graph convolutional networks （RGCNs） is proposed. By analyzing the various working modes of multi-function radar， the method enables parallel data processing and addresses the interactions between different working modes and their characteristic parameters.

Modulation Type Recognition of Radar PRI Based on Multi-feature Combination

Junchen LIU, Bo YAN, Chunlei ZHAO, Wenzhong ZHOU

2025, 53(1): 129-139. doi:10.3969/j.issn.1009-086x.2025.01.014

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A multi-feature joint method for radar pulse repetition interval （PRI） modulation type recognition is proposed to address the challenges of low recognition accuracy， significant impacts from pulse loss and false pulses， and sensitivity to decision threshold settings in existing types. First， the concept of density clustering is employed to remove irrelevant pulses， enabling the preprocessing of the pulse train and mitigating the effects of pulse loss and spurious pulses on pulse train patterns. Statistical methods are then applied to extract the stability features， second-order differential variation features， continuity features and pulse pair matching features of signal time difference. Finally， a random forest algorithm is used to train and test the extracted features. The simulation results demonstrate that the proposed method achieves high recognition accuracy for PRI modulation types and exhibits robust resistance to pulse loss and spurious pulses.

Research on Echo Detection Method of Non-cooperative Hybrid Bistatic SAR

Wenlei SUN, Rongjun GU, Yonghai WANG, Zhizeng ZHOU

2025, 53(1): 140-146. doi:10.3969/j.issn.1009-086x.2025.01.015

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The real-time detection of scene echoes is a prerequisite for beam synchronization in spaceborne/airborne hybrid bistatic synthetic aperture radar （SAR）. To address the issues of weak scene echoes， range migration， and energy dispersion in hybrid bistatic SAR， a frequency-domain M/N detection method based on the analysis of scene scattering characteristics and echo models is proposed. The method leverages the correlation of adjacent PRF scenes to aggregate scene energy， effectively mitigating the impact of range migration. Simulation and experimental results demonstrate that the proposed algorithm achieves a high detection probability and superior performance compared to conventional detection algorithms. In addition， it offers strong resilience to jamming， low computational complexity， and is suitable for real-time implementation， making it practical for engineering applications.

Study of the Capacity Loss and Improvement Methods of Lithium-Boron Thermal Batteries

Zhiqiang ZHAN, Mingcan WANG, Huaijie JIA, Shuying DONG, Yujiang CUI

2025, 53(1): 147-153. doi:10.3969/j.issn.1009-086x.2025.01.016

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Thermal batteries are widely used in various weapon systems due to their advantages， such as fast activation， long storage life， and a wide operating temperature range. However， compared to short-duration thermal batteries， long-duration thermal batteries often exhibit significant capacity loss. The mechanism of capacity loss in long-duration lithium-boron thermal batteries is investigated. The findings indicate that cathode materials with high thermal stability benefit performance during both high- and low-temperature discharges. However， mature thermal battery cathodes currently cannot withstand thermal shock. The dissolution and diffusion of the anode are identified as key factors contributing to the capacity loss. Improvement measures to address these issues are proposed.

Integrated Design Method of Lifting Device Based on Hydraulic Cylinder Performance Model

Zhaoyu NIU, Chengqian SU, Pengfei GAO

2025, 53(1): 154-163. doi:10.3969/j.issn.1009-086x.2025.01.017

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The traditional design process for vertical lifting devices involves verifying the feasibility of the layout design through a single scheme for the hydraulic cylinder. This process does not fully leverage the coupling relationship between the layout parameters and hydraulic cylinder performance， making it difficult to achieve rapid design and optimization. The design and calculation process of the hydraulic cylinder is mathematically modeled to calculate its performance characteristics， which are then used to construct a hydraulic cylinder performance model. By incorporating this model into the design process of the vertical lifting device， a direct mapping relationship between the layout scheme and hydraulic cylinder performance is established， enabling an integrated design of both. In addition， an application study is presented， where the integrated design method is used to quickly calculate the performance parameters of hydraulic cylinders for a given layout scheme. How changes in the layout scheme affect the hydraulic cylinder’s performance parameters is also investigated. The findings provide a foundation for the rapid design and optimization of lifting devices.

Method for Transmission of Point Cloud and Tele-presence of Map Under Wireless and Low Bandwidth Condition

Xinyu LIU, Haiting SHEN, Rui GUO, Qin ZHANG

2025, 53(1): 164-172. doi:10.3969/j.issn.1009-086x.2025.01.018

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Intelligent unmanned weapons and equipment are playing an increasingly vital role in modern warfare and have become essential for replacing and assisting soldiers in combat. In unmanned battlefields， rear commanders monitor the battlefield environment through communication. Given the limited bandwidth of military communication equipment， a method for real-time point cloud transmission and remote map presentation is proposed and implemented. The method first estimates the real-time pose using the FAST-LIO algorithm， then compresses the 3D point cloud （keyframe） using the Draco algorithm， and transmits the real-time pose and point cloud via Protobuf-UDP. Finally， the SC-PGO algorithm is used to optimize and generate the global map. This is the first engineering solution to achieve real-time point cloud compression and transmission based on the ROS platform. The experimental results demonstrate that the proposed method provides effective compression and stable transmission quality for real-time point clouds， addressing the challenges of point cloud transmission and remote map presentation under low-bandwidth wireless conditions， and enabling commanders to perceive the battlefield environment in real time.

Research on Equipment Support Unit Effectiveness Evaluation Based on Entropy Weighting-subjective and Objective Weighting Method

Hao HU, Fuzhou FENG, Junzhen ZHU, Junfeng HAN

2025, 53(1): 173-181. doi:10.3969/j.issn.1009-086x.2025.01.019

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An effectiveness evaluation method for the mobility capability of a certain type of equipment is proposed to address the uncertainty and imprecision of evaluation indicators that affect the results. The subjective-objective weighting method， entropy weighting method， and cloud model are applied to comprehensively assess the mobility effectiveness of the equipment. An evaluation model for mobility effectiveness is developed， and the basic steps of the evaluation process are discussed. The evaluation results are expressed in the form of a cloud-based membership function. The method provides an intuitive evaluation of the equipment’s mobility effectiveness. Case study results demonstrate that this method can effectively assess the mobility efficiency of the equipment and support decision-making in mobility planning.

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