An improved adaptive navigation algorithm based on adjustable student-t distribution in an urban environment

Ying Zhang; Zhe Yang; Hongbo Zhao; Tao Yang; Wenquan Feng

doi:10.1117/12.2627428

14 February 2022 An improved adaptive navigation algorithm based on adjustable student-t distribution in an urban environment

Ying Zhang, Zhe Yang, Hongbo Zhao, Tao Yang, Wenquan Feng

Author Affiliations +

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 1216109 (2022) https://doi.org/10.1117/12.2627428
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

Aiming at the problem that the abnormal values of the measurement noise appear when GPS signals become weak or disappear in the urban environment, which reduces the positioning accuracy of the INS/GPS tight coupled navigation system, an improved adaptive filtering algorithm based on the adjustable Student-t distribution is proposed. This method uses Student-t distribution to model the measurement noise, the Mahalanobis distance of innovation vector to adjust filter’s adaptation, and the variational Bayesian method to better track changes in measurement noises. Experimental results show that the method can achieve a more robust estimation result and a better positioning effect in an urban environment.

Citation Download Citation

Ying Zhang, Zhe Yang, Hongbo Zhao, Tao Yang, and Wenquan Feng "An improved adaptive navigation algorithm based on adjustable student-t distribution in an urban environment", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 1216109 (14 February 2022); https://doi.org/10.1117/12.2627428

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