A novel robust iterated CKF for GNSS/SINS integrated navigation applications

In challenging circumstances, the estimation performance of integrated navigation parameters for tightly coupled GNSS/SINS is impacted by outlier measurements. An effective solution that employs a novel iterative sigma-point structure with a modified robustness optimization approach for enhancing th...

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Bibliographic Details
Published inEURASIP journal on advances in signal processing Vol. 2023; no. 1; pp. 83 - 18
Main Authors Wang, Junwei, Chen, Xiyuan, Shi, Chunfeng
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.12.2023
Springer
Springer Nature B.V
SpringerOpen
Subjects
Approximation
Control theory
Data analysis
Engineering
Error compensation
Global navigation satellite system
GNSS challenge conditions
Iterated CKF
Kalman filters
Optimization
Outlier measurement
Outliers (statistics)
Parameter estimation
Quantum Information Technology
Robust estimation
Signal processing
Signal,Image and Speech Processing
Spintronics
Robust estimation
Iterated CKF
GNSS challenge conditions
Outlier measurement
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Summary:In challenging circumstances, the estimation performance of integrated navigation parameters for tightly coupled GNSS/SINS is impacted by outlier measurements. An effective solution that employs a novel iterative sigma-point structure with a modified robustness optimization approach for enhancing the error compensation effectiveness and robustness of filters utilized in GNSS challenge conditions is proposed in this paper. The proposed method modifies the CKF scheme by incorporating nonlinear regression and numerous iteration processes for ameliorating error compensation. Subsequently, a loss function and penalty mechanism are implemented to enhance the filter's robustness to outlier measurements. Furthermore, to fully incorporate valid information of the innovation and speed up the operation of the proposed method, the outlier measurement detection criteria are established to bypass the penalty mechanism against measurement weights in the absence of outliers in GNSS measurements. Field experiments demonstrate that the proposed method outperforms traditional methods in mitigating navigation errors, particularly when multipath errors and non-line-of-sight (NLOS) reception are increased.
ISSN:1687-6180
1687-6172
1687-6180
DOI:10.1186/s13634-023-01044-9