Table of Content

28 April 2026, Volume 54 Issue 2

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REVIEW ARTICLE PAPERS

REVIEW ARTICLE

Review of Technological Development and Trends of Foreign Shipboard Missile Launchers

Qiang GUO, Zhiyan ZHANG, Jian LI, Huiguo QIN, Xueming PENG

2026, 54(2):  1-12.  doi:10.3969/j.issn.1009-086x.2026.02.001

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Shipboard missile launching systems have become the primary weaponry systems for modern naval vessels. Their technological level， structural configuration， and production costs directly impact the operational effectiveness， technical performance， and combat paradigms of entire shipborne systems. This paper presents the evolutionary process of technological iterations in international shipborne missile launch systems， outlines the technical characteristics， advantages， and limitations of typical launch systems， and comprehensively discusses the advantages， applications， and current developmental status of modular launch systems in foreign naval surface launch technologies. Based on future combat paradigms， missile launch requirements， and technological trends， the paper analyzes the key development directions and trends for shipboard missile launch systems， particularly modular systems， in the evolution of surface launching technologies.

Review of Image Restoration Methods Based on Lucky Imaging

Pin LÜ, Yiquan WU

2026, 54(2):  13-33.  doi:10.3969/j.issn.1009-086x.2026.02.002

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Lucky imaging constitutes a pivotal approach for restoring turbulence-degraded imagery. Recent advances have explored method optimizations across diverse application scenarios. However， existing reviews published years ago do not cover breakthroughs from the past decade. This study conducts a thorough investigation of cutting-edge algorithms， first introducing classical methodologies and outlining persistent challenges. We then elaborate on the developments and applications through three dimensions： real-time implementation， multi-target adaptability， and integration with complementary image processing techniques. A dedicated turbulence dataset is released alongside systematic analysis of benchmark datasets， evaluation metrics， and comparative performance of leading methods. Scenario-specific applicability and inherent limitations are analyzed， culminating in six future trajectories： GPU-edge heterogeneous computing， dynamic turbulence modeling with non-stationary compensation， data-driven end-to-end fusion， multi-modal cross-scale restoration， event-camera-based dynamic imaging， and standardized evaluation frameworks with open-source ecosystems.

Overview of Military Simulation Experiment Technology

Zhen ZHAO, Xiaolin ZHAO, Maolin GAO, Jie MIN, Weikang CHEN

2026, 54(2):  34-47.  doi:10.3969/j.issn.1009-086x.2026.02.003

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Currently， countries worldwide attach great importance to the development and application of military simulation experiment technology， which plays a key role in improving combat capability， supporting equipment demonstration， promoting the innovation of tactics and methods， optimizing joint operation processes， and supporting technology research， development， and verification. This paper provides an in-depth analysis of military simulation experiment technology. It first elucidates the core concepts， logical processes， and the close connections among model classifications. Then， starting from the top-level architecture of military simulation software， it deeply analyzes mainstream simulation engines， frameworks， and typical systems to demonstrate their support for military simulation experiment technology. Finally， it explores the application prospects of new technologies such as artificial intelligence and the Metaverse in military simulation， comprehensively presenting the overall architecture and development trajectory of military simulation experiment technology.

PAPERS

Threat Assessment of Penetrating Counter Air Platforms Based on Combination Weighting TOPSIS

Menggao TAO, Bingqie WANG, Qingxin ZHANG, Wenjie WEI, Jide TANG, Wensi HE

2026, 54(2):  48-60.  doi:10.3969/j.issn.1009-086x.2026.02.004

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To address the multidimensional threats posed by the U.S. air force's penetrating counter air （PCA） operational system to China's air defense security， this study resolves the evaluation bias caused by the imbalance between subjective and objective weights in traditional threat assessment methods by innovatively constructing a “combined weighting TOPSIS” evaluation model. An assessment framework encompassing seven core metrics—including collaborative command and control effectiveness， electromagnetic suppression capability， and fire strike effectiveness—is established based on PCA operational characteristics. Subsequently， the entropy weight method is employed to quantify objective weights for platform intrinsic attributes， while the eigenvector method is utilized to derive subjective weights reflecting tactical intent. A game theory-based deviation minimization algorithm is introduced to achieve Nash equilibrium optimization of the combined subjective-objective weights. PCA platform threat assessment model is developed using the technique for order preference by similarity to ideal solution （TOPSIS）， enabling the prioritization of PCA platform threats. Case simulation results validate the effectiveness of this threat assessment methodology， which provides a reference framework for evaluating incoming PCA platform threats in counter-penetration operations.

Target Association Method for IFF Based on Evidence Theory

Shanyong YAN

2026, 54(2):  61-68.  doi:10.3969/j.issn.1009-086x.2026.02.005

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To address the problem of association between IFF targets and radar targets in scenarios dense target scenarios， an association method based on evidence theory is proposed. A positional correlation model is established. Evidence and its basic probability assignment （BPA） are generated based on the azimuth and range measurement capabilities of the radar and IFF interrogator， as well as data from multiple measurements. Evidence derived from multiple measurements of the same target is combined using the Dempster rule to construct a combined evidence set. The association of all targets is completed sequentially based on a maximum value search within the combined evidence set. The simulation results demonstrate that， the proposed method achieves higher association accuracy than the nearest neighbor （NN） method at equivalent time complexity. Furthermore， compared to the Kuhn-Munkres （KM） algorithm， the proposed method achieves higher accuracy in most dense target scenarios with lower time complexity.

Target Assignment and Fire Scheduling Method for Unmanned Combat Systems

Peilin LI, Jie GUO, Xifeng CHEN, Yangyang WAN, Shengjing TANG

2026, 54(2):  69-81.  doi:10.3969/j.issn.1009-086x.2026.02.006

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To address the real-time and efficiency requirements for multi-target cooperative interception by unmanned combat systems in dynamic battlefield scenarios， this paper proposes a greedy target assignment and fire scheduling method based on dynamic time window （GTAFS-DTW）. By constructing a relative motion model between combat units and targets， the proposed method incorporates engagement distance constraints， task execution constraints， and target maneuver characteristics. a dynamic time window screening mechanism is designed with the optimization objective of minimizing engagement time and impact time difference. On this basis， a hierarchical greedy strategy is adopted to prioritize unit-target pairs with overlapping feasible engagement intervals， and temporal cooperative optimization is achieved through iterative adjustment of window boundaries and fire scheduling. Simulation results demonstrate that GTAFS-DTW effectively reduces impact time deviation to within 0.5 s in both lateral and longitudinal queue scenarios compared with traditional discrete particle swarm optimization （DPSO）， significantly enhancing computational efficiency and satisfying real-time optimization requirements.

Study on Prograde and Retrograde Orbit Interception Based on the Adjoint Method

Yadong CHEN, Bo LÜ, Tianzhu REN, Junhui LIU

2026, 54(2):  82-91.  doi:10.3969/j.issn.1009-086x.2026.02.007

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In view of the effect of different prograde and retrograde rendezvous modes on miss distance， the vehicle terminal guidance rendezvous process is modeled and analyzed based on the theory of adjoint method. The original model of the terminal guidance problem is established， and the adjoint model of the problem is established based on the adjoint method. Normalized analytical expressions for the influence of factors such as target maneuver and initial heading error on miss distance were obtained. Based on the above theoretical analysis， the characteristics of reverse orbit head-on rendezvous， pursuit following orbit rendezvous and forward following orbit rendezvous are summarized.

A Method for Rapid Acquiring and Tracking Hypersonic Cooperative Targets

Jingxiao LI, Gege TIAN, Guanghui XU, Chenglu ZHAO, Jing LUO

2026, 54(2):  92-99.  doi:10.3969/j.issn.1009-086x.2026.02.008

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Aiming at the urgent requirements of guidance radar to guide hypersonic weapons to intercept incoming targets in fiercely air-to-ground military confrontation， rapid acquisition and tracking technologies are studied. There are several problems need to be solved： one is the RCS of hypersonic missiles/shells is small that not easy to acquire， the second is the hypersonic missiles/shells flight speed is high and has a wide speed distribution that difficult to detect and track. The problems are solved from three aspects： radar system design， waveform design and tracking model design. Through the design of radar operating system based on narrowband signal processing and PD processing， the influence of range migration is reduced， and the detectability of dim target under strong clutter background is improved. Through the design of guidance waveform based on double PRF（pulse repetition frequency） sets， the velocity ambiguity in Doppler is resolved. Through the design of search interception screen based on prior information and the design of taking velocity into track initiation and track correlation model， the rapid acquisition and stable tracking of hypersonic cooperative targets are realized. The effectiveness of the proposed model is fully verified in the semi-physical simulation test.

Analysis of the Impact of Aircraft Kinematic State on Radar Detection Probability

Kunkun LI, Haiqing LUO, Zijing LIU, Tianxiang LIU

2026, 54(2):  100-109.  doi:10.3969/j.issn.1009-086x.2026.02.009

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Maintaining a low detection probability by defense radars in vital areas is a fundamental requirement for aircraft route planning during aerial surveys. This necessitates considering and assessing the variations in radar detection probability caused by the kinematic state uncertainty of the aircraft itself. To this end， analysis method based on unscented transformation （UT） is proposed to evaluate the impact of aircraft kinematic state uncertainty on detection probability. Relevant models regarding aircraft detection by radar are presented. The UT method is introduced to establish an process for the propagation of aircraft kinematic state （involving position， and attitude） uncertainty and their impact on radar detection probability. A simulation experiment scenario is designed wherein an aerial survey aircraft is detected by a single-pulse defense radar. The Monte Carlo method is employed to verify the high analysis accuracy of the UT method. Additionally， the patterns regarding how varying degrees of aircraft kinematic state uncertainty affect detection probability are analyzed. Furthermore， comparisons with the traditional linear covariance analysis method demonstrate that the UT method possesses both simplicity and high computational efficiency.

Research on Aerial Target Position Tracking for IFF Interrogator Antenna

Xuehai TU

2026, 54(2):  110-117.  doi:10.3969/j.issn.1009-086x.2026.02.010

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In response to the issues of inaccurate tracking of aerial moving targets and signal quality degradation caused by pitch， roll， and heading disturbances affecting the interrogator antenna of the identification friend or foe （IFF） system， this paper proposes and designs a dual-motor coordinated PID control method with feedforward compensation based on motion twist for target position calculation. The method calculates the target’s coordinates using azimuth， distance， and elevation angle data provided by the radar. Pitch， roll， and heading disturbance signals are embedded into the target position through motion twist transformation， with the resulting azimuth and elevation angles serving as control commands. The derivative of these commands is used as feedforward compensation to enhance system response speed. Simulation results demonstrate that this approach effectively mitigates the three types of ship attitude disturbances and enables rapid and precise tracking of aerial targets.

Anomaly Detection in Radar Reconnaissance Signals Using Multidimensional Temporal Intelligence Fusion Network

Linxuan HUANG, Minghao HE, Chunlai YU, Mingyue FENG, Fuqun ZHANG, Yinan ZHANG

2026, 54(2):  118-127.  doi:10.3969/j.issn.1009-086x.2026.02.011

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Addressing the issue of data anomalies in radar countermeasure reconnaissance signals caused by susceptibility to interference in complex electromagnetic environments， this paper proposes a multidimensional temporal intelligent fusion network （MDTFusionNet）. The architecture integrates temporal convolutional network（TCN）， long short-term memory（LSTM）， and self-attention mechanisms with a gated network that dynamically adjusts module weights through a gated network， and optimizes model robustness by combining weight sparsity constraints. This constructs an anomaly detection model capable of not only capturing short-term fluctuations in radar signals and grasping long-term trends but also dynamically focusing on critical pulse information. To verify its effectiveness， multi-layer perceptron（MLP）， TCN， and LeNet networks are used for comparison， and evaluations are conducted from the perspectives of loss function and accuracy. Experimental results show that the loss function outliers of MDTFusionNet are significantly smaller than those of traditional models， and the accuracy is higher. Ablation studies further confirm that each component in MDTFusionNet has its respective role， enabling better learning of temporal data feature distributions and accurate anomaly detection， verifying its superiority and practicality in radar countermeasure reconnaissance signal anomaly detection.

Specific Emitter Identification Algorithm Based on Sample Alignment and Semi-global Attention Mechanism

Zhiqiang ZHANG, Jin HU, Jinxin XU, Yunsong WU

2026, 54(2):  128-136.  doi:10.3969/j.issn.1009-086x.2026.02.012

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To address the issues of incomplete data cleaning mechanisms for specific emitter signals and insufficient adaptive feature representation capability leading to low individual recognition rates， this paper proposes an individual identification algorithm incorporating sample alignment and a semi-global attention mechanism. During the data preprocessing stage， the main components of specific emitter intermediate frequency （IF） signals are extracted through multi-condition dual-threshold processing， enabling arrival time synchronization across samples. Subsequently， multi-dimensional feature alignment operations， including pulse width alignment and amplitude normalization， are performed， ensuring the cleaned samples gain generalization capability for individuals with identical frequency points. A semi-global attention mechanism is introduced and integrated with a dual-channel convolutional neural network （CNN）， strengthening the network's feature representation capacity while maintaining training efficiency. This mechanism combines semi-global geometric similarity with learnable similarity measures， employing parallel processing of sparse attention scores to preserve long-range feature dependencies， thereby achieving more accurate feature details and higher computational efficiency. Experimental results on measured specific emitter signal datasets indicate that the proposed method effectively address the challenges of uneven data distribution and inadequate adaptive feature representation， significantly improving model recognition accuracy.

Bayesian Regularization Design Method for Test Samples of Multi-sensitive Factor Anti-suppression Interference

Lin GENG, Jinxi HAN, Jianguang JIA, Yihui LIN, Zhiwen XU, Rui ZHAO

2026, 54(2):  137-146.  doi:10.3969/j.issn.1009-086x.2026.02.013

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To improve the anti-interference test capability of missiles in complex electromagnetic environments， this paper proposed a Bayesian regularization design method for test samples of multi-sensitive factor anti-suppression interference. First， this method analyzed the typical multi-sensitive factors affecting the anti-suppression interference capability of the seeker and then designed a Bayesian regularization network to solve the test sample design problem of missile anti-interference. The constructed Bayesian regularization network for multi-sensitive factor anti-suppression interference tests could establish a nonlinear mapping relationship between different multi-sensitive anti-interference influencing factors and anti-interference capability， greatly reducing the sample size of traditional all-factor traversal tests. Then， the hyperparameter solving method for the constructed network was studied， thereby realizing the Bayesian regularization design method for test samples. Finally， simulation experiments on typical anti-suppression interference were conducted to verify the performance of the proposed test sample design method. The results indicate that the Bayesian regularization test sample design for multi-sensitive factor anti-suppression interference effectively shortens the time cycle， saves test resources， and provides theoretical support for the anti-interference test evaluation of precision-guided missiles.

Radar Signal Sorting Algorithm Based on Convex Clustering and AMA Optimization

Yue FAN, Yongxiang ZHANG, Yajun FANG

2026, 54(2):  147-154.  doi:10.3969/j.issn.1009-086x.2026.02.014

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A radar signal sorting algorithm based on convex clustering is proposed to address the issues of existing radar signal sorting algorithms that rely on manually preset number of clusters and are sensitive to initial input values. Convex clustering algorithm is a clustering analysis method based on objective function， which can ensure the global optimal solution of radar signal sorting task by optimizing the convex objective function， and the clustering effect is independent of radar signal input. After standardizing the pulse description word （PDW） output by the interception receiver， construct a convex optimization objective function and solve it using alternating minimization algorithm to obtain the final sorting result. Simulation experiments show that the radar signal sorting algorithm based on convex clustering achieves high sorting accuracy， while maintaining good stability and noise robustness.

Radar Working State Assessment Based on Adaptive Augmented Bayesian

Yongwei LU, Huan LIN, Yinbing ZHANG, Shihao SHAN, Shiju YANG

2026, 54(2):  155-162.  doi:10.3969/j.issn.1009-086x.2026.02.015

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Aiming at the requirements of adaptive adjustment of jamming strategies according to radar behaviors and real-time evaluation during radar countermeasures， an evaluation method based on the fusion of AdaBoost algorithm and Naive Bayes classifier is proposed to meet the requirements of adaptive adjustment and real-time evaluation of interference strategy with radar behavior during radar countermeasures. This method extracts features from the time domain， frequency domain， modulation domain， and polarization domain of radar signals， using a naive Bayes classifier as the base classifier. Through AdaBoost iteration and dynamic feedback scaling adjustment of difficult to distinguish sample weights， the accuracy and stability of the model evaluation ability are enhanced. Simulation experiments have shown that the performance of this algorithm is superior to typical algorithms. This study provides an optimized solution for real-time quantitative evaluation of radar interference effects in complex electromagnetic environments， which can be applied to intelligent interference decision-making in radar countermeasures.

Multi-modal Collaborative EMP Protection Architecture for UAV Electromechanical Servo Systems

Guoliang SUN, Xu ZHANG, Shiyao GAO, Wei LIAO

2026, 54(2):  163-172.  doi:10.3969/j.issn.1009-086x.2026.02.016

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Aiming at the reliability challenges of mid-to-low-end UAV servos in strong electromagnetic pulse （EMP） environments， traditional static protection models employing simple technical superposition have limitations in adapting to dynamic strong electromagnetic environments. To overcome this limitation， this study innovatively proposes a “dynamic weight allocation—auxiliary fault-tolerant” collaborative protection architecture by introducing time-varying weight coefficient to achieve dynamic perception of EMP and adjust filtering and reconstruction strategies. First， considering that manufacturing defects and structural gaps in the material shielding layer can lead to attenuation of shielding effectiveness （SE）， the model of the silver/copper nanowire gradient coating was correspondingly revised based on experimental data inversion. Subsequently， an adaptive notch filtering algorithm based on dynamic filtering technology was employed to further suppress residual noise. Simulation and experimental results demonstrate that the proposed multimodal coupling method of material shielding， dynamic filtering， and dynamic reconstruction significantly enhances the electromagnetic interference protection of UAV servos， increasing the anti-interference performance from 31.5 dB with single shielding effectiveness to 93 dB.

Research on Maintenance Interval Optimization Method for Flight Test

Yuwen GUO

2026, 54(2):  173-180.  doi:10.3969/j.issn.1009-086x.2026.02.017

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During the aircraft flight test， maintenance activities are one of the main factors leading to aircraft unavailability. Currently， scheduled maintenance still accounts for a large proportion of preventive maintenance activities. Therefore， conducting research on maintenance interval optimization methods is of great significance for not only improving the quality and efficiency， reducing risks of flight test， but also guiding maintenance work. By comparing the differences between flight test and civil aircraft operations， a maintenance interval optimization method including steps such as data collection and preprocessing for a series of aircraft models， data fusion， modeling and verification， and determination of maintenance interval is constructed. Based on flight test data， the correctness and engineering applicability of this method are demonstrated， providing methodological support for maintenance interval optimization.

Model Construction of the Aerospace Equipment Maintenance Support Chain

Zijian ZHANG, Yongfu ZHANG, Rui SUN, Dong CHEN

2026, 54(2):  181-191.  doi:10.3969/j.issn.1009-086x.2026.02.018

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Space equipment maintenance support is the core of space equipment support activities， the effectiveness of maintenance support directly affects the achievement of space equipment support tasks and expected combat objectives. With the subtle transformation of battlefield morphology and situation， the position of aerospace equipment in integrated joint operations is becoming increasingly prominent， fast response guarantee， agile guarantee， precise guarantee， and uninterrupted guarantee have become major issues that urgently need to be broken through and solved. This article takes the maintenance and support chain of aerospace equipment as the starting point， on the basis of its concept， explain its characteristics， and based on platform element integration， business process planning and other logical frameworks， as well as analogy model methods， constructing a maintenance and support chain model for aerospace equipment. The research content provides a research approach for improving the maintenance support capabilities of aerospace equipment， at the same time， for the construction of maintenance and support forces in other branches of the military， and the integrated and unified construction of joint operations has a guiding role and reference basis.

Research on Characteristics and Credibility Evaluation of Digital-Real Integrated Parallel Simulation

Jinxi HAN, Lin GENG, Jianguang JIA, Jun XU, Zilong WANG

2026, 54(2):  192-197.  doi:10.3969/j.issn.1009-086x.2026.02.019

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With the emergence of simulation applications such as digital parallel battlefields， equipment digital twins， and digital-real fusion tests， based on a comprehensive analysis of the development trends of modern military simulation technologies and systems， this paper focused on the main characteristics of the LVC（live virtual construstion）-based digital-real integrated parallel simulation system and the new problems emerging in its credibility evaluation. Moreover， it proposed a corresponding credibility evaluation framework to help enhance the credibility of complex simulation systems in fields such as military training and military exercises.