低温等离子体用于高功率微波防护研究

等离子体对于高功率微波的攻击具有独特的防护效果。基于等离子体流体近似方法，利用COMSOL软件研究了高功率微波与柱状等离子体阵列相互作用过程中入射电场随时间的演变过程，分析了等离子体防护高功率微波的物理过程和作用机理。研究结果表明，入射的高功率微波会使等离子体参数发生剧烈变化，特别是其电子密度将急剧增加，从而使等离子体对入射的高功率微波表现出类似金属的电磁特性，最终实现对入射高功率微波的有效防护。此外，利用高频辉光放电产生柱状等离子体阵列，通过实验验证了等离子体对高功率微波的防护作用。最后，总结了基于等离子体的高功率微波防护技术需解决的主要问题。

Study of high-power microwave protection technology based on low-temperature plasma

Aiming at the problem that the accuracy of the existing modulation signal recognition model was low under the condition of weak supervision with only a small amount of labeled data, a semi supervised learning framework based on generated countermeasure network was proposed. By performing a redundant spatial transformation on the communication signals, the method can adapt to the generative adversarial network model and retain rich signal adjacent features. Through the introduction of Wasserstein generative adversarial network-gradient penalty, a semi-supervised learning framework suitable for electromagnetic signal processing was constructed to realize the effective utilization of unlabeled signal samples. In order to verify the effectiveness of the proposed algorithm, sufficient experiments were conducted on the RADIOML 2016.04C dataset. Experimental results show that the proposed method can train an efficient classifier under semi-supervised conditions and obtain excellent modulation recognition results.