DocumentCode :
1994003
Title :
Exterior orientation elements´ Bayesian estimation model under insufficient ground control points
Author :
Luo, Xiaobo ; Liu, Qiang ; Liu, Qinhuo
Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
fYear :
2010
fDate :
18-20 June 2010
Firstpage :
1
Lastpage :
5
Abstract :
It is crucial to estimate the exterior orientation elements accurately when carrying out geometric positioning based on geometric imaging model. Currently, least-squares method is widely adopted for the estimation of exterior orientation elements. However, in the absence of sufficient ground control points, least-squares estimation is not convergent. Therefore, we proposed a Bayesian estimation model for inversing exterior orientation elements in case of insufficient ground control points. In this study, according to scanning imaging mechanism, a geometric imaging model of geostationary satellites was established. A detailed theoretical inference of Bayesian estimation was then carried out from the geometry imaging model. A simulation experiment was finally conducted using randomly simulated ground control points. The experimental results showed that, in case of few ground control points, Bayesian estimation could also get accurate exterior orientation elements and had good positioning accuracy as well.
Keywords :
Bayes methods; artificial satellites; computational geometry; geophysics computing; least squares approximations; Bayesian estimation model; exterior orientation elements; geometric imaging model; geometric positioning; geostationary satellites; ground control points; least squares method; scanning imaging mechanism; Bayesian methods; Computational modeling; Estimation; Imaging; Mathematical model; Remote sensing; Satellites; Bayesian; Geostationary Satellite; Insufficient Ground Control Points; exterior orientation elements;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics, 2010 18th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-7301-4
Type :
conf
DOI :
10.1109/GEOINFORMATICS.2010.5567615
Filename :
5567615
Link To Document :
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