DocumentCode
2437694
Title
Algorithmic Research of Data Fusion in Mixed Navigation System Based on Least-Square Method
Author
Yun, Chen ; Jijing, Wang
Author_Institution
Sch. of Commun. & Transp. Eng., Changsha Univ. of Sci. & Technol., Changsha
Volume
2
fYear
2008
fDate
19-20 Dec. 2008
Firstpage
286
Lastpage
289
Abstract
To advance the vehicle setting accuracy, mixed navigation system emerges as the times require. The keystone of mixed navigation research is how to make use of multi-sensor´s locator data effectively. Multi-sensor data fusion technology is an innovation for data processing developed recently, and data fusion method research is paid close attention to generally. The classical linearity least-squares estimation is linearity unbiased and its variance identity. This paper presented a mixed navigation system data fusion method based on least-square estimation, which focused on multi-positioning system´s sense data. And it also demonstrated its effectiveness of algorithm through emulation counting.
Keywords
least squares approximations; radionavigation; sensor fusion; data fusion; data processing; least-square method; mixed navigation system; multipositioning system; vehicle setting accuracy; Base stations; Filtering algorithms; Global Positioning System; Kalman filters; Least squares methods; Linearity; Navigation; Nonlinear equations; Sensor systems; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3490-9
Type
conf
DOI
10.1109/PACIIA.2008.331
Filename
4756782
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