Application of Adaptive Robust Kalman Filter Base on MCC for SINS/GPS Integrated Navigation

Linfeng Li, Jian Wang, Zhiming Chen, Teng Yu*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

In this paper, an adaptive and robust Kalman filter algorithm based on the maximum correntropy criterion (MCC) is proposed to solve the problem of integrated navigation accuracy reduction, which is caused by the non-Gaussian noise and time-varying noise of GPS measurement in complex environment. Firstly, the Grubbs criterion was used to remove outliers, which are contained in the GPS measurement. Then, a fixed-length sliding window was used to estimate the decay factor adaptively. Based on the fixed-length sliding window method, the time-varying noises, which are considered in integrated navigation system, are addressed. Moreover, a MCC method is used to suppress the non-Gaussian noises, which are generated with external corruption. Finally, the method, which is proposed in this paper, is verified by the designed simulation and field tests. The results show that the influence of the non-Gaussian noise and time-varying noise of the GPS measurement is detected and isolated by the proposed algorithm, effectively. The navigation accuracy and stability are improved.

源语言英语
文章编号8131
期刊Sensors
23
19
DOI
出版状态已出版 - 10月 2023

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Li, L., Wang, J., Chen, Z., & Yu, T. (2023). Application of Adaptive Robust Kalman Filter Base on MCC for SINS/GPS Integrated Navigation. Sensors, 23(19), 文章 8131. https://doi.org/10.3390/s23198131