DocumentCode
3227444
Title
Estimation covariance of measurement fusion on track-to-track problem
Author
Xue-bo, Jin ; You-xian, Sun
Author_Institution
Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
Volume
3
fYear
2002
fDate
28-31 Oct. 2002
Firstpage
1650
Abstract
Measurement fusion is an optimal data fusion algorithm. The covariance of measurement fusion is proved to be decided by a function of the measurement matrix and measurement noise covariance. The greater the function is, the less the covariance measurement fusion method can obtain. Therefore, the estimation accuracy increases when the function increase. The results of simulation agree with the theoretical results.
Keywords
covariance matrices; measurement errors; optimisation; sensor fusion; estimation accuracy; estimation covariance; measurement fusion; measurement matrix; measurement noise covariance; optimal data fusion algorithm; simulation results; track-to-track problem; Covariance matrix; Erbium; Estimation error; Filters; Maximum likelihood estimation; Noise measurement; Sensor fusion; State estimation; Sun; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN
0-7803-7490-8
Type
conf
DOI
10.1109/TENCON.2002.1182649
Filename
1182649
Link To Document