Recursive target identification fusion methods based on Dezert-Smarandache theory
基于Dezert-Smarandache理论的递归目标识别融合方法

Target identification is a major practical application of information fusion, in which Dezert-Smarandache theory (DSmT) is a useful method for dealing with problems with uncertainties and is efficient in combining conflicting evidences. We put forward three temporal-spatial information fusion approaches including the centralized fusion approach, the distributed approach without-feedback and the distributed approach with-feedback. Especially, when integrity constraints are introduced to the system, it is necessary to employ the conflict distance parameter to determine the combination order of evidences. This will in some extent overcome the deficiency in noncommitative property in the hybrid DSm rule of combination. Numerical examples are provided to show the validity in applications of the proposed approach.