A matching-unscented Kalman filtering for gravity aided navigation

Lin Wu; Xin Tian; Hong Ma; Jinwen Tian

doi:10.1117/12.901640

8 December 2011 A matching-unscented Kalman filtering for gravity aided navigation

Lin Wu, Xin Tian, Hong Ma, Jinwen Tian

Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 80030P (2011) https://doi.org/10.1117/12.901640
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

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.

Citation Download Citation

Lin Wu, Xin Tian, Hong Ma, and Jinwen Tian "A matching-unscented Kalman filtering for gravity aided navigation", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030P (8 December 2011); https://doi.org/10.1117/12.901640

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