DocumentCode :
1802271
Title :
Research of observation model error for dynamic navigation
Author :
Yalin Jiao ; Gao, Shesheng ; Feibiao Song
Author_Institution :
Northwestern Polytechnical University, Xi´an, China
fYear :
2013
fDate :
1-8 Jan. 2013
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a new random weighting method to estimate the systematic error of the observation model for dynamic navigation. This method randomly weights the covariance matrices of predicted residual vector and observation vector to control their magnitudes for resisting the disturbances of the observation model error on state parameter estimation. Random weighting theories are established to estimate the covariance matrices of predicted residual vector and observation vector. It is also rigorously proved that the random weighting estimation of the systematic error for observation model is unbiased. Experiments and comparison analysis demonstrate that the proposed random weighting method can effectively resist the disturbances of observation model noise, thus improving the accuracy of dynamic navigation significantly.
Keywords :
Covariance matrices; Estimation; Kalman filters; Kinematics; Navigation; Systematics; Vectors; dynamic navigation; observation model error; random weighting estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
Type :
conf
DOI :
10.1109/ANTHOLOGY.2013.6784829
Filename :
6784829
Link To Document :
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