A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of applications. Conflict management is an open issue in Dempster-Shafer evidence theory. In this paper, a novel multi-sensor data fusion approach is proposed based on the spectral angle cosine function of evidence, belief entropy and group decision fuzzy preference relation analysis. The numerical simulation analyses demonstrate that the improved DS evidence theory available in this paper overcomes the limitations of conventional DS evidence theory, and can realizes more reliable fusion with multi-sensor conflicting information compared to the existing methods.