A weighted fusion algorithm of multi-sensor based on optimized grouping

被引：0
|
作者：
Zhang, Liyong [1 ]
Li, Dan [1 ]
Zhang, Li [1 ]
Zhong, Chongquan [1 ]
机构：
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian, Liaoning, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
optimized grouping; weighted fusion; maximum likelihood principle; partheno-genetic algorithm; optimal estimation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：5350 / +
页数：2
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