Jiang Wen, Zhuang Miaoyan, Xie Chunhe
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel). 2017 Jul 5;17(7):1575. doi: 10.3390/s17071575.
Multi-sensor data fusion technology based on Dempster-Shafer evidence theory is widely applied in many fields. However, how to determine basic belief assignment (BBA) is still an open issue. The existing BBA methods pay more attention to the uncertainty of information, but do not simultaneously consider the reliability of information sources. Real-world information is not only uncertain, but also partially reliable. Thus, uncertainty and partial reliability are strongly associated with each other. To take into account this fact, a new method to represent BBAs along with their associated reliabilities is proposed in this paper, which is named reliability-based BBA. Several examples are carried out to show the validity of the proposed method.
基于Dempster-Shafer证据理论的多传感器数据融合技术在许多领域得到了广泛应用。然而，如何确定基本置信分配（BBA）仍然是一个悬而未决的问题。现有的BBA方法更多地关注信息的不确定性，但没有同时考虑信息源的可靠性。现实世界中的信息不仅是不确定的，而且部分是可靠的。因此，不确定性和部分可靠性彼此密切相关。考虑到这一事实，本文提出了一种表示BBA及其相关可靠性的新方法，称为基于可靠性的BBA。通过几个例子验证了该方法的有效性。
