Knowledge Graph Based Adversarial Radar Threat Assessment

Chenyu Zhu, Yue Li, Xinyue Hou, Peng Wang, Xiaoyan Peng
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Abstract

In the field of military equipment knowledge, there are a large number of equipment models, weapon types, working parameters, and other time-frequency-space data information, among which there is a lot of valuable information. At present, when combat-related personnel face this massive knowledge, they cannot efficiently obtain the key knowledge, which means that they cannot provide effective guidance based on the potential key knowledge. To solve this problem, based on the investigation and analysis of the existing knowledge graph construction method, we excavate and extract military equipment knowledge, instantiate and correlate different weapon equipment, and construct the knowledge graph of military equipment. Its construction can not only deeply study the key technical difficulties of the graph in this field, but also has strong strategic support for the future development of this field. In the end, we propose a threat assessment for target radar with a TransE inference model based on the knowledge graph.
基于知识图谱的对抗雷达威胁评估
在军事装备知识领域,存在着大量的装备型号、武器类型、工作参数等时频空数据信息,其中有很多有价值的信息。目前,作战人员在面对海量的关键知识时,无法高效获取关键知识,也就是说,无法根据潜在的关键知识进行有效的指导。为解决这一问题,在调查分析现有知识图谱构建方法的基础上,挖掘和提取军事装备知识,实例化和关联不同武器装备,构建军事装备知识图谱。它的构建不仅可以深入研究该领域的关键技术难点,而且对该领域的未来发展具有强有力的战略支撑。最后,提出了一种基于知识图的TransE推理模型的目标雷达威胁评估方法。
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