An integrated adaptive Kalman filter for improving the reliability of navigation systems
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Ali Almagbile
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Jinling Wang
Abstract
Integrated GPS/INS using Kalman filter is the best technique for improving navigation accuracy. Assuming that the covariance matrices are known and constant, a conventional Kalman filter (CKF) is usually used, however, when they are unknown and time-varying, several adaptive estimation approaches have to be developed to estimate the statistical information of the measurement (R), process (Q), and state (P) covariance matrices. In many situations, blunders/faults in the measurement model and/or sudden changes in the dynamic model may occur during the navigation period. Therefore, the CKF, as well as the adaptive Kalman filter (AKF) will exhibit abnormal behavior and may lead the filter to be suboptimal or even diverge. In this study, the Sage-Husa adaptive Kalman filter (SHAKF) and innovation-based adaptive Kalman filter (IAKF) approaches are employed for adapting the measurement covariance matrix(R). In the case of abrupt changes in the dynamic model, the state covariance matrix (P) is adapted using the strong tracking filter (STF). The performance of these adaptive approaches is evaluated before and after simulating a fault of different sizes in the measurement and dynamic models. The results show that with a large window width, the SHAKF outperforms the CKF and IAKF. However, when the system encounters any fault either in the measurement or dynamic model, the SHAKF loses its optimality and diverges. The sensitivity of the SHAKF to the fault is because the R matrix accumulates with the propagation of the recursive noise estimator. On the other hand, the IAKF and STF provide better performance than both the CKF and SHAKF because the gain matrix is adaptively adjusted to mitigate the influence of the fault, and therefore, they behave normally when a fault of any size occurs in the measurement and/or dynamic model.
Funding source: Yarmouk University
Award Identifier / Grant number: Unassigned
Acknowledgments
The authors would like to thank the anonymous reviewers for their constructive comments on the submitted manuscript. Many thanks to Yarmouk University for facilitating the procedures to conduct this research and for partly covering the APC.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This research received no external funding
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Conflicts of interest statement: The authors declare no conflict of interest. The roles in the collection, analysis, or interpretation of data; in the writing of the manuscript, and the decision to publish the results are solely by the authors.
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Data availability statement: The data presented in this study are available upon request from the first author.
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© 2023 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Review
- Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration
- Original Research Articles
- Solution for ill-posed EIV model regularization attending to its decreasing regularization characteristic
- Trajectory evaluation using repeated rail-bound measurements
- Global geopotential models evaluation based on terrestrial gravity data over Ethiopia
- A calculation method for GNSS positioning precision based on the posteriori unit weight variance
- Accuracy and reliability of BeiDou clocks
- Positioning performance with dual-frequency low-cost GNSS receivers
- Estimating 3D displacement vectors from line-of-sight observations with application to MIMO-SAR
- Determination of the height reference surface for the Republic of Albania by using global geopotential models
- An integrated adaptive Kalman filter for improving the reliability of navigation systems
Artikel in diesem Heft
- Frontmatter
- Review
- Investigation of the trade-off between the complexity of the accelerometer bias model and the state estimation accuracy in INS/GNSS integration
- Original Research Articles
- Solution for ill-posed EIV model regularization attending to its decreasing regularization characteristic
- Trajectory evaluation using repeated rail-bound measurements
- Global geopotential models evaluation based on terrestrial gravity data over Ethiopia
- A calculation method for GNSS positioning precision based on the posteriori unit weight variance
- Accuracy and reliability of BeiDou clocks
- Positioning performance with dual-frequency low-cost GNSS receivers
- Estimating 3D displacement vectors from line-of-sight observations with application to MIMO-SAR
- Determination of the height reference surface for the Republic of Albania by using global geopotential models
- An integrated adaptive Kalman filter for improving the reliability of navigation systems
