Research on Multi-Source Information Fusion System Based on Wavelet Neural Network and Evidential Theory
Kun Huang · Shuju caiji yu chuli · 2003
In order to solve general phenomena of uncertainty, unintegrity and redundancy in the multi source information fusion, firstly using a phase reconstruction theory, input information is reconstructed in the phase space and correlative information in the input information is extracted. Then using fuzzy theory, wavelet neural network and genetic algorithm, the above reconstructed information is fused from the time domain in the reconstructed phase space. Finally, using a D S evidence theory, result of the time domain fusion is fused from the space domain, and decision making is also done by a rule of decision making. Practical application shows that the distributed multi source information fusion system based on the ideology has famous capability for target detection, resisting the environmental disturbance and fault tolerance.