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
Link To Document :
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