融合粗糙集和DS方法的空中目标类型识别算法

Recognition algorithm of aerial targets type integrating rough set and DS theory

通过分析粗糙集和Dempster-shafe(DS)方法在描述不确定信息上的相似性,将这两种理论融合建立统一框架,提出了融合粗糙集和DS方法的空中目标类型识别算法.该算法通过知识库推导得出基本概率分配函数,采用基于粗糙集的信任函数作为可信度度量,使得改进后的算法更有理论深度.实验结果表明,算法具有良好的运行效果.

Based on analyzing the similarity of rough set and Dempster-shafe （DS） evidence theory, a recognition algorithm of aerial targets type integrating the two theories is proposed. In the algorithm, basic probability assignment function can be deduced from platform database, and the rough belief function is taken as the reliability measure, which is more theoretical than ever. Experiments show that the algorithm has satisfying recognition results.