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论文类型：会议论文

发表时间：2006-06-21

收录刊物：EI、CPCI-S、Scopus

卷号：2

页面范围：5350-+

关键字：optimized grouping; weighted fusion; maximum likelihood principle; partheno-genetic algorithm; optimal estimation

摘要：When measuring a certain state, multi-sensor can be divided, into several groups, then processed by grouping weighted fusion algorithm. Based on the measurement equation of the state :and the model of the noise, optimal weights of grouping fusion algorithm can be obtained by the principle of maximum likelihood estimation, and optimal grouping way of multi-sensor can be constructed by parthenogenetic algorithm. According to the methods mentioned above, a weighted, fusion algorithm of multi-sensor based on optimized grouping is presented in the paper, which can achieve the optimal estimation of the state to be measured.