|Table of Contents|

Consensus Multi-sensor Data Fusion Algorithm Based onDynamic Hierarchical Clustering Analysis(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2018年04期
Page:
87-
Research Field:
·数学与计算机科学·
Publishing date:

Info

Title:
Consensus Multi-sensor Data Fusion Algorithm Based onDynamic Hierarchical Clustering Analysis
Author(s):
Zhou Zhenjuan1; Diao Lianwang2
(1.College of Electronic and Information Engineering,Jiangsu Open University,Nanjing 211135,China)(2.S & T on Information System Engineering Lab.,The 28th Research Institute of CETC,Nanjing 210007,China)
Keywords:
hierarchical clustering; data fusion; degree of confidence; connection matrix
PACS:
TN911.2
DOI:
10.3969/j.issn.1001-4616.2018.04.014
Abstract:
To improve the precision of multi-sensor data fusion method,in the procedure of data fusion,the reliability of sensor data must be considered. The shortcomings of the existing consensus multi-sensor data fusion algorithms,such as asymmetry of distance matrix,and subjectivity of connection matrix are discussed,and a new confidence distance is defined. The common mean of some normal distributions are estimated by maximum likelihood method,and its statistical and recursive characters are derived. A consensus multi-sensor data fusion algorithm based on dynamic hierarchical clustering is proposed. The example shows that this method is better than the existing methods.

References:

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Last Update: 2018-12-30