【摘要】 在战场目标价值分析和打击目标排序分析过程中，为了构建敌方作战目标体系，需要分析战场目标间的关联关系。轨迹和部署数据中隐藏大量信息，提出了一种从轨迹和部署数据中挖掘出感兴趣的目标关系类型信息的方法，所提方法对轨迹部署数据进行时空聚类，从聚类结果提取目标；对聚类目标使用频繁项挖掘算法分析挖掘满足一定支持度的有关联关系的目标，再根据构建的关系类型知识库或关系规则，分析目标间的具体关系类型。所提方法能对积累的目标历史轨迹部署数据分析挖掘出目标间的关联关系，挖掘出目标潜在的关系类型可为后续构建目标体系提供关系数据。更多还原

【Abstract】 In the analyzing process of the value of battlefield targets and the ranking of attacking targets, it is necessary to analyze the correlation between battlefield targets in order to construct an enemy combat target system.Since a large amount of information is hidden in trajectory and deployment data, a method is proposed for mining interesting target relationship type information from the data.First, the data clusters spatiotemporally, and targets are extracted from clustering results.The frequent item mining algorithms are used for clustering targets to analyze and mine related targets with a certain level of support.Then the specific relationship types between targets are also analyzed based on the established relationship type repository or relationship rules.On the basis of the accumulated historical trajectory deployment data of the targets, the method proposed can analyze and mine the correlation between targets.The mined potential relationship types of targets can provide the relationship data for building the target system in the future.更多还原