一种基于度量层信息的基本信任分配构造方法

在决策层融合目标识别中，Dempster组合规则是一种常用的融合算子，它的有效应用取决于相应基本信任分配的合理建立。该文针对决策层融合目标识别问题中子源传感器输出的度量层信息，分析了基本信任分配的构造准则，并提出了一种基于参考向量与度量层信息之间相似度的基本信任分配构造方法。在仿真数据与空中雷达目标实测数据上的实验结果表明，该方法构造的基本信任分配能够有效地通过Dempster组合规则进行融合。

A Basic Belief Assignment Construction Method Based on the Information of Measurement Level

Dempster rule of combination is a useful fusion operator for decision level recognition fusion. The effective application of this rule depends on the rational construction of corresponding basic belief assignment. Considering the measurement information from each sensor in decision level recognition fusion, this paper suggests a group of principles for constructing basic belief assignment, and then presents a strategy of basic belief assignment construction based on the similarity degree between referential vector and the measurement information. The experiments on artificial data and real data of radar aerial target demonstrate the basic belief assignments constructed by the presented method can be fused by Dempster rule of combination effectively.