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在多源信息融合中 ,不确定、不完整和冗余现象普遍存在。为了解决这个复杂问题 ,本文首先利用相空间重构理论对输入的信息在相空间中进行重构 ,以充分提取相关信息。然后在重构相空间上 ,利用模糊理论、小波网络和遗传算法对上述重构信息进行了时间域信息融合。最后 ,利用 D-S证据理论将时间域融合结果进行了空间域信息融合 ,并根据决策规则进行了决策。结果表明 ,据此形成的分布式多源信息融合系统具有良好的目标探测能力、抗干扰能力和容错能力
In multi-source information fusion, the phenomena of uncertainty, incompleteness and redundancy are ubiquitous. In order to solve this complex problem, this paper firstly reconstructs the input information in phase space by using phase space reconstruction theory to extract the relevant information. Then on the reconstructed phase space, fuzzy theory, wavelet network and genetic algorithm are used to fuse the above reconstructed information in time domain. Finally, using the D-S evidence theory, the spatial domain information fusion is made based on the fusion results of the time domain and the decision is made according to the decision rules. The results show that the distributed multi-source information fusion system has good target detection capability, anti-interference ability and fault tolerance