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Research on Characteristics and Credibility Evaluation of Digital-Real Integrated Parallel Simulation
Jinxi HAN, Lin GENG, Jianguang JIA, Jun XU, Zilong WANG
Modern Defense Technology    2026, 54 (2): 192-197.   DOI: 10.3969/j.issn.1009-086x.2026.02.019
Abstract15)   HTML1)    PDF (852KB)(13)       Save

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.

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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
Modern Defense Technology    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.

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