Track correlation uncertainty evaluation for Multi-sensor Data Fusion System and its application

Author(s):  
Shiyou Chen ◽  
Hao Liu ◽  
Hou Xiao
2013 ◽  
Vol 706-708 ◽  
pp. 644-649
Author(s):  
Shu Ying Li ◽  
Mu Qin Tian ◽  
Lei Xue

The multi-sensor data fusion widely applied to military and industry areas is a new technique developed in recent years. It can avoid the limitations of a single sensor and obtain more information, improving the recognition ability. This paper analyzes the uncertainties in the traditional earlier period diagnosis in induction motors based on the single parameter and introduces the idea of using multi-sensor data fusion to handle these uncertainties. In a fusion system several parameters will be fused according to the D-S evidential fusion algorithm in order to identify accurately the earlier period faults of the induction motors. Practical diagnostic examples show that the fault diagnostic accuracy and confidence are markedly promoted by using the multi-sensor data fusion.


2011 ◽  
Vol 58-60 ◽  
pp. 1548-1553
Author(s):  
Ning Ning Qin ◽  
Wen Yi Shen ◽  
Jun Yan ◽  
Bao Guo Xu

Through investigating the architecture of multi-sensor data fusion system, a universal software architecture which can be used in distributed multi-radar fusion systems is proposed in this paper. In this architecture, functionally independent modules will be extracted from system, it will be standardized as components by object-oriented techniques, and the interface specifications of all the modules are also specified. Aiming at the different objects, system flow and modules can be framed quickly by selecting or expanding proper components based on different scenes feature and object properties. The architecture improves software reusability and scalability, and is propitious to increase software development efficiency.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 147349-147357 ◽  
Author(s):  
Fuqin Deng ◽  
Yongshen Huang ◽  
Song Lu ◽  
Yingying Chen ◽  
Jia Chen ◽  
...  

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