|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.|
Proceedings of the ION 2017 Pacific PNT Meeting
May 1 - 4, 2017
Marriott Waikiki Beach Resort & Spa
|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.
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