一种基于证据理论和模糊集合的信息融合方法

针对证据理论应用中基本概率分配函数难以确定和多传感器之间相互支持程度计算绝对化的问题,提出了一种基于证据理论和模糊集合(FSB-DS)的信息融合方法。该方法首先利用相关性函数定义不确定信息的模糊支持区间和模糊支持概率,然后由隶属函数得到各个传感器提供信息的可信度,再将支持度和可信度转化为基本概率分配函数,最后进行D-S证据合成。仿真实验表明,该方法获得的结果具有更高的精度和可信度。

Information Fusion Method Based on Proof Theory and Fuzzy Set

Focused on the problem that it is difficult to set up the basic probability assignment function in the evidence theory and the calculation of degree of mutual support is absolute, an information fusion method based on evidence theory and fuzzy set（FSB-DS） is proposed. The fuzzy support range and the fuzzy support probability is obtained from the correlation function.. Then by using the membership fizaction, the reliability of information provide by each sensor is gained, and then transform support and credibility into basic probability assignment function, and finally the DS evidence combination. The simulation results shows that the fusion results have higer precision and reliability compared with other methods.