DocumentCode
2247404
Title
Data Fusion with Different Accuracy
Author
Tang, Jin ; Gu, Jason ; Cai, Zixing
Author_Institution
Dept. of Electr. & Comput. Eng., Dalhonsie Univ., Halifax, NS
fYear
2004
fDate
22-26 Aug. 2004
Firstpage
811
Lastpage
815
Abstract
This paper presents criteria to evaluate different data fusion approaches. A new fusion method for two data with different accuracy is also presented. This approach is an extension of weighted average, which can solve some problem that cannot be handled by maximum likelihood approach. Simulation result is compared with other three fusion algorithms. Comparison shows that it is better than all weighted average approaches and it is the best of these four approaches
Keywords
maximum likelihood detection; sensor fusion; data fusion; maximum likelihood; Data engineering; Fuses; Gaussian distribution; Information science; Random variables; Remote sensing; Sensor systems; Data fusion; Minimum expectation; Uniform distribution; Weighted average;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on
Conference_Location
Shenyang
Print_ISBN
0-7803-8614-8
Type
conf
DOI
10.1109/ROBIO.2004.1521888
Filename
1521888
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