New algorithm to select false evidence and its application in multi-sensor data fusion

Dempster Shafer theory of evidence is widely used in data fusion due to its flexibility to deal with uncertain information processing. However, Dempster's rule of combination cannot efficiently handle conflict between the various information sources. In this paper, a novel method to identify the false evidence is proposed. First, the distance function between bodies of evidence is introduced to express the degree of conflict degree. Then, the confidence lever of each piece of evidence is obtained to reflect the reliability of each information source to some degree. By setting a threshold, the false evidence can be determined. The numerical example of multi-sensor fusion target recognition based on DS theory is shown to illustrate the efficiency of the presented approach.