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发表时间：2008-01-01

发表刊物：仪器仪表学报

所属单位：电子信息与电气工程学部

期号：1

页面范围：200-205

ISSN号：0254-3087

摘要：When measuring a certain state with multi-sensor, the multi-sensor can be divided into groups and then processed by grouping weighted fusion algorithm, which can obtain relatively accurate estimation of the state to be measured. However the estimation effects are different greatly due to different combination ways of multi-sensor. In this paper, how to divide the sensors properly in grouping fusion algorithm is discussed, and the grouping principle is summarized based on the number of sensors in each group and the magnitude relationship of the measurement noise variance of the sensors in different groups. Using the proposed principle the estimated fusing value can reach an optimal point. Then, we extract the mathematical model of this principle, and prove theoretically the least variance characteristic of the grouping fusion algorithm, which is based on the optimal grouping principle. The optimal grouping principle provides a theoretical basis for evaluating and choosing the ways of grouping properly. Finally, an example is presented, which indicates that optimal grouping principle greatly shortens the areas in searching the optimal ways of grouping and can effectively solve the blindness about the problem of how to group, accordingly, optimal online grouping can be realized by this grouping principle when multi-sensor is used in measurement task.

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