基于队形的聚合解聚方法研究

Aggregation and Disaggregation Methods Research Based on Formation

多分辨率建模的一个重要应用是聚合解聚,而聚合解聚的核心问题是使不同分辨率层次的模型彼此之间的映射关系真实有效,要求属性间关联合理,并能保持属性映射的一致性。因此,从一种常用的多分辨率模型——作战编队模型的队形属性出发,对如何提高聚合解聚的真实性进行探讨。详细分析了位置、状态、战损三种常用属性和队形在聚合解聚过程中的依赖关系,通过补充附加存储结构,合理利用标准队形数据库的方法减少模型失真,基于此设计了一组聚合解聚算法。实验结果表明本算法对队形和三种常用属性的聚合解聚关系的分析合理,并且能更好地抑制解聚过程中的模型失真,使模型间的属性一致性得到增强。

The method of aggregation and disaggregation is an essential application of multi-resolution modeling. The key issue is how to maintain the effective mapping relations between the corresponding attributes of different resolution level, which contains the rational relationship between different attributes, and consistency maintenance of attributes. Based on formation, the key attribute of formation multi- resolution models, of how to promote the reality in aggregation and disaggregation process was analyzed in the work. The dependency relationship between formation and three typical attributes： position, combat status and damage was analyzed, and by designing an additional dynamic storage structure, the necessary information for model property consistency models was reduced, and a new algorithm for the three attributes was designed. Combining the application of databases, the experiment shows the better effects on consistency maintenance between disaggregation results, namely, the enhancement of consistency.