A Robust Tracking Loop Using Adaptive H∞ Unscented Kalman Filter in GNSS Receivers

In the context of complex dynamic environments, a robust tracking loop is essential for achieving accurate positioning with GNSS receivers. The tracking loop based on the Kalman filter significantly improves the tracking accuracy and dynamic performance. However, Kalman filtering relies on accurate...

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Bibliographic Details
Published inInternational Conference on Indoor Positioning and Indoor Navigation pp. 1 - 6
Main Authors Gao, Ning, Chen, Xiyuan, Wang, Yuetong, Jiao, Zhiyuan, Shi, Chunfeng, Yan, Zhe
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.10.2024
Subjects
Accuracy
Filtering theory
Global navigation satellite system
GNSS receivers
Kalman filters
nonlinear filter
Receivers
robust filter
Robustness
Satellites
tracking loop
Tracking loops
Uncertainty
Vehicle dynamics
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Summary:In the context of complex dynamic environments, a robust tracking loop is essential for achieving accurate positioning with GNSS receivers. The tracking loop based on the Kalman filter significantly improves the tracking accuracy and dynamic performance. However, Kalman filtering relies on accurate prior knowledge to achieve optimal estimation. In practical applications, satellite signals are subject to various uncertainties, which can severely degrade tracking performance. To enhance tracking robustness, this paper proposes an adaptive \boldsymbol{H}_{\infty} unscented Kalman filter (AHUKF) based on robust control theory. By utilizing the correlator output as measurement information, a tracking loop is devised based on AHUKF to effectively mitigate the impact of unknown signal noise statistics in complex scenarios. Field vehicle experiment demonstrates that the proposed method effectively suppresses the impact of external interference on the tracking loop, thereby indirectly enhancing receiver accuracy.
ISSN:2471-917X
DOI:10.1109/IPIN62893.2024.10786182