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Proceedings Paper

A matching-unscented Kalman filtering for gravity aided navigation
Author(s): Lin Wu; Xin Tian; Hong Ma; Jinwen Tian
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Paper Abstract

A matching-unscented Kalman filtering for gravity aided navigation is presented in this paper. With this method submerged position fixes for autonomous underwater vehicle can be obtained from comparing gravity fields' measurements with gravity maps, meanwhile the drawback of traditional matching or filtering algorithms can be avoided. A synthetic gravity map was taken for the simulation, and the results showed that navigation errors can be reduced more efficiently and reliably by the presented method.

Paper Details

Date Published: 8 December 2011
PDF: 5 pages
Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030P (8 December 2011); doi: 10.1117/12.901640
Show Author Affiliations
Lin Wu, Huazhong Univ. of Science and Technology (China)
Institute of Geodesy and Geophysics (China)
Xin Tian, Huazhong Univ. of Science and Technology (China)
Hong Ma, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8003:
MIPPR 2011: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Nong Sang, Editor(s)

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