Research on Information Fusion of Two New DLL Discriminator Algorithms

Abstract

After information fusion model has been established, the feature-level fusion algorithm based on fuzzy neural network and expert system is proposed, in which the expert system has been embedded into fuzzy neural network so that it could choose the membership function and adjust the network structure. At the same time, for code tracking loop, two new code phase discriminator algorithms based on DLL structure is proposed. Evidence theory has been applied to achieve the decision-making level fusion. The performances of the two algorithms were studied by using theoretical method and experimental method with analog IF signal data and actual IF signal data respectively. Then, the results of feature-level fusion have been taken as the evidences to construct the frame of discernment. The research results show that the process of information fusion has abilities of adapting and self-learning.