A new weighted classifier combination method with two-step evidential discounting operations

In target recognition, multi-source fusion, such as multiple radar fusion has to be considered to achieve accurate identification. In classification fusion problem, the classifiers are often considered with different weights. DS rule is used for optimizing the classifier weights. The evidence discounting operation with classifier weights can improve the classifier reliability. However, the classification results of different patterns by a common classifier may also have different reliability. Thus, evidence distance and conflict are used to determine the pattern weights. Some real data sets are used to test the proposed method, and results show that the proposed method can efficiently improve the classification accuracy.