Release Time:2019-03-12  Hits:

Indexed by: Conference Paper

Date of Publication: 2006-06-21

Included Journals: Scopus、CPCI-S、EI

Volume: 2

Page Number: 5350-+

Key Words: optimized grouping; weighted fusion; maximum likelihood principle; partheno-genetic algorithm; optimal estimation

Abstract: 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.