Architectures and application of data fusion system based on nervous system evolution

摘要

An evolution model of data fusion system based on evolution procedure of nervous system is proposed. There are lots of similar characteristics between the evolution of nervous system and the development of data fusion system. It is reasonable to try to find guidelines in the theory of nervous system. For example, the function and structure of data fusion nodes almost take a same role as neurons in nervous system do, so we name the data fusion nodes as data fusion units. Just as the nervous system, the basic evolution architectures of data fusion system include four phases: Chaos (Autonomous), Fully Distributed, Centralized, and Internal Model Based Hierarchical. In the last phase of evolution, interface among unites becomes independent intelligent parts step by step. It provides a more flexible hierarchical data fusion architecture, which makes it be possible to simulate the regulation and adaptation mechanism of nervous system. The application analyses of these mechanisms to the data fusion systems proved that this dynamic hierarchy architecture is capable of deciding not only what to fuse and how to fuse but also when to fuse.