Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter
This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/10/2372 |
| _version_ | 1798035322861256704 |
|---|---|
| author | Antônio C. B. Chiella Bruno O. S. Teixeira Guilherme A. S. Pereira |
| author_facet | Antônio C. B. Chiella Bruno O. S. Teixeira Guilherme A. S. Pereira |
| author_sort | Antônio C. B. Chiella |
| collection | DOAJ |
| description | This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow variations in the measurement uncertainty. To deal with slow time-varying perturbations in the sensors, an adaptive strategy based on covariance matching that tunes the measurement covariance matrix online is used. Additionally, an outlier detector algorithm is adopted to identify abrupt changes in the UKF innovation, thus rejecting fast perturbations. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as external magnetic field interference and linear accelerations. Comparative experimental results that use an industrial manipulator robot as ground truth suggest that our method overcomes a trusted commercial solution and other widely used open source algorithms found in the literature. |
| first_indexed | 2024-04-11T20:56:38Z |
| format | Article |
| id | doaj.art-85073812887046e6b8b727ea78310790 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T20:56:38Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-85073812887046e6b8b727ea783107902022-12-22T04:03:40ZengMDPI AGSensors1424-82202019-05-011910237210.3390/s19102372s19102372Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman FilterAntônio C. B. Chiella0Bruno O. S. Teixeira1Guilherme A. S. Pereira2Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Hotizonte 31270-901, BrazilGraduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Hotizonte 31270-901, BrazilDepartment of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV 26506-6070, USAThis paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow variations in the measurement uncertainty. To deal with slow time-varying perturbations in the sensors, an adaptive strategy based on covariance matching that tunes the measurement covariance matrix online is used. Additionally, an outlier detector algorithm is adopted to identify abrupt changes in the UKF innovation, thus rejecting fast perturbations. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as external magnetic field interference and linear accelerations. Comparative experimental results that use an industrial manipulator robot as ground truth suggest that our method overcomes a trusted commercial solution and other widely used open source algorithms found in the literature.https://www.mdpi.com/1424-8220/19/10/2372unit quaternionunscented Kalman filterMARG sensoradaptive filtering |
| spellingShingle | Antônio C. B. Chiella Bruno O. S. Teixeira Guilherme A. S. Pereira Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter Sensors unit quaternion unscented Kalman filter MARG sensor adaptive filtering |
| title | Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter |
| title_full | Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter |
| title_fullStr | Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter |
| title_full_unstemmed | Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter |
| title_short | Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter |
| title_sort | quaternion based robust attitude estimation using an adaptive unscented kalman filter |
| topic | unit quaternion unscented Kalman filter MARG sensor adaptive filtering |
| url | https://www.mdpi.com/1424-8220/19/10/2372 |
| work_keys_str_mv | AT antoniocbchiella quaternionbasedrobustattitudeestimationusinganadaptiveunscentedkalmanfilter AT brunoosteixeira quaternionbasedrobustattitudeestimationusinganadaptiveunscentedkalmanfilter AT guilhermeaspereira quaternionbasedrobustattitudeestimationusinganadaptiveunscentedkalmanfilter |