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A Novel Adaptive Factor-Based H∞ Cubature Kalman Filter for Autonomous Underwater Vehicle
| Content Provider | MDPI |
|---|---|
| Author | Zhang, Aijun Wu, Yixuan Zhi, Chenbo Yang, Rui |
| Copyright Year | 2022 |
| Description | In the navigation of an autonomous underwater vehicle (AUV), the positioning accuracy and stability of the navigation system will decrease due to uncertainties such as mobility, inaccuracy of a priori process noise characteristic, and simplification of a dynamic model. In order to solve the above problems, a new, adaptive factor-based H∞ cubature Kalman filter based on a fading factor (AF-H∞CKF) is proposed in this paper. On the one hand, the H∞ game theory provides AF-H∞CKF good robustness in the worst case; on the other hand, the fading factor makes the innovation orthogonal and inflates the predicted error covariance and the Kalman gain, which avoids a decrease in estimation precision in the case of model uncertainty. The simulation and experiment results show that the AF-H∞CKF filter can deal with AUV navigation better than other existing algorithms in the presence of outliers and model uncertainty, which confirms its effectiveness and superiority. |
| Starting Page | 326 |
| e-ISSN | 20771312 |
| DOI | 10.3390/jmse10030326 |
| Journal | Journal of Marine Science and Engineering |
| Issue Number | 3 |
| Volume Number | 10 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-02-25 |
| Access Restriction | Open |
| Subject Keyword | Journal of Marine Science and Engineering Industrial Engineering Marine Engineering Autonomous Underwater Vehicle Adaptive Factor Cubature Kalman Filter |
| Content Type | Text |
| Resource Type | Article |
