30 October 2009 Gravity gradient-terrain aided navigation based on particle filter
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Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74984A (2009) https://doi.org/10.1117/12.832523
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
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.
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Ling Xiong, Ling Xiong, Jie Ma, Jie Ma, Jin-Wen Tian, Jin-Wen Tian, "Gravity gradient-terrain aided navigation based on particle filter", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74984A (30 October 2009); doi: 10.1117/12.832523; https://doi.org/10.1117/12.832523
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