Data Fusion Technology Research Demonstrates C3i Data Integration Program

C3I(Command, Control, Communication and Intelligence ) systems play an very important role in modern warfare because they can help people to make full use of information and weapons, enhance battle effectiveness. Data fusion technique synthesizes data from multiple sensors and related information from associated databases, to achieve improved accuracies and more specific inferences than those could be achieved by the use of a single sensor alone. It is actually an important part of current C3I systems and its process model contains the signal detection, position, identity assessment in low level and the situation assessment and the threat assessment in high level. Meanwhile, it is also the integration of many traditional disciplines and new areas of engineering.Based on analyzing of characteristics of current C3I systems and limitations of old C3I systems, neural network and fuzzy reasoning technologies are introduced into C3I data fusion system. Moreover, in order to solve real-time, fault tolerance and uncertain reasoning problems of C3I systems, an architecture of C3I systems based on the above new idea is proposed. And then, this idea is applied to the multi-sensor multi-target tracking system and its algorithms, such as data relation, and identification, are discussed in this thesis. The main contributions are as follows:1) History of C3I systems and development of data fusion in C3I systems are discussed in details. Then three core technologies, which are data fusion technology, neural network technology and fuzzy reasoning technologies are focused.2) According to analyzing of characteristics of current C3I data fusion and limitations of data fusion and advantages of neural network, a conceptual model build on neural network is proposed.3) After analyzing advantage and disadvantage of neural network and fuzzy reasoning, a project to solve real-time, fault tolerance and uncertain reasoning problems of C3I systems and a data fusion architecture of C3I systems are proposed.4) Based on the above architecture introduced in this thesis, two key parts of the multi-sensor multi-target tracking system of C3I systems, which are data relation and identification, are discussed in details.