Target recognition fusion based on the largest degree of membership and evidence theory

The type and precision of sensors,outside interference,and different sensitivity of different sensors to different target may all have effect on the result of target recognition.A target recognition fusion model based on the largest degree of membership and evidence theory was set up by applying the correlative knowledge of intelligent information processing and multi-source information fusion.Firstly,each factor that has influence on target recognition was analyzed in the model;then different weights are selected in each radar station according to the largest degree of membership.The degree of membership of the measured target relative to the reference target in the target-base is gained,and then the decision results are sent to the fusion center. D-S evidence theory was studied,and its evidential combination formula and decision formula were analyzed.In the fusion center,D-S evidence theory was used to implement data fusion,and the target recognition decision results were obtained finally.An example demonstrated that the target recognition fusion model is feasible.