Kalman Filter Based Partial Ambiguity Resolution Methods for Relative Positioning

Y. Arakawa, K. Abe, Y. Kubo and S. Sugimoto

Peer Reviewed

Abstract:	In this paper, Kalman filter based relative positioning algorithms with partially integer ambiguity resolution are proposed. In the methods, the partially fixed ambiguity is utilized as a pseudo measurement to update the estimate and its covariance matrix of the Kalman filter. And the updated estimate and its covariance matrix can effectively improve the convergence time as well as the positioning accuracy of the Kalman filter. The performances of the proposed methods as well as positioning accuracy are examined by using real receiver data.
Published in:	Proceedings of the ION 2017 Pacific PNT Meeting May 1 - 4, 2017 Marriott Waikiki Beach Resort & Spa Honolulu, Hawaii
Pages:	191 - 201
Cite this article:	Arakawa, Y., Abe, K., Kubo, Y., Sugimoto, S., "Kalman Filter Based Partial Ambiguity Resolution Methods for Relative Positioning," Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, May 2017, pp. 191-201. https://doi.org/10.33012/2017.15083
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