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Proceedings Paper

Gravity gradient-terrain aided navigation based on particle filter
Author(s): Ling Xiong; Jie Ma; Jin-Wen Tian
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Paper Abstract

Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain elevation data. The position can be actualized through matching the real-time measured gravity gradient data to the prepared gravity gradient reference map. The most widely used approximate filtering method is the extended Kaman filter (EKF). EKF is computationally simple but, the convergence of the state estimation for the position is not guaranteed. Particle filter (PF) makes use of the non-linear state and measurement functions, no linearization technology is needed. PF can assure the convergence of the state estimation which follows from the classical results on convergence of Bayesian estimators. Simulations have been done and Particle filter has been shown to be a superior alternative to the EKF in the gravity gradient-terrain matching navigation systems.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74984A (30 October 2009); doi: 10.1117/12.832523
Show Author Affiliations
Ling Xiong, Huazhong Univ. of Science and Technology (China)
Wuhan Univ. of Science and Technology (China)
Jie Ma, Huazhong Univ. of Science and Technology (China)
Jin-Wen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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