Title: Improved Ambiguity Searching Method of Ultra-Short Baseline with Nonlinear Constraint
Author(s): Hang Guo, Baolian Tian, Min Yu, Linkun Deng, Haitao Wang
Published in: Proceedings of the 2018 International Technical Meeting of The Institute of Navigation
January 29 - 1, 2018
Hyatt Regency Reston
Reston, Virginia
Pages: 46 - 55
Cite this article: Guo, Hang, Tian, Baolian, Yu, Min, Deng, Linkun, Wang, Haitao, "Improved Ambiguity Searching Method of Ultra-Short Baseline with Nonlinear Constraint," Proceedings of the 2018 International Technical Meeting of The Institute of Navigation, Reston, Virginia, January 2018, pp. 46-55.
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Abstract: The success rate of the ambiguity solution can be improved with a baseline length constraint. The performance of the traditional ambiguity resolution method may be degraded by the remainder term of linear approximation for ultra-short baselines. In this paper, an algorithm for the nonlinear constraint of baseline length has been proposed. It searches the optional solution for the objective function satisfying the baseline verification in the space constructed with the LAMBDA method. Compared with the algorithm without constraint and the linear constraint of baseline length, the success rate of the proposed algorithm increased significantly. In our tests, the success rates of static ambiguity fixation have been increased by 30% - 40%, while the dynamic example shown the ambiguity fixation success rate increased by 60% -70%.