Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF
Optimal two stage Kalman filter (OTSKF) is able to obtain optimal estimation of system states and bias for linear system which contains random bias. Unscented Kalman filter (UKF) is a conventional nonlinear filtering method which utilizes Sigmas point sampling and unscented transformation technology...
| Format: | Article |
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| Language: | zho |
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EDP Sciences
2018-10-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p933.pdf |
| _version_ | 1797668855963713536 |
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| collection | DOAJ |
| description | Optimal two stage Kalman filter (OTSKF) is able to obtain optimal estimation of system states and bias for linear system which contains random bias. Unscented Kalman filter (UKF) is a conventional nonlinear filtering method which utilizes Sigmas point sampling and unscented transformation technology realizes propagation of state means and covariances through nonlinear system. Aircraft is a typical complicate nonlinear system, this paper treats the faults of Inertial Measurement Unit (IMU) as random bias, established a filtering model which contains faults of IMU. Hybird the two stage filtering technique and UKF, this paper proposed an optimal two stage unscented Kalman filter (OTSUKF) algorithm which is suitable for fault diagnosis of IMU, realized optimal estimation of system states and faults identification of IMU via proposed innovative designing method of filtering model and the algorithm was validated that it is robust to wind disterbance via real flight data and it is also validated that proposed OTSUKF is optimal in the existance of wind disturbance via comparing with the existance iterated optimal two stage extended kalman filter (IOTSEKF) method. |
| first_indexed | 2024-03-11T20:35:35Z |
| format | Article |
| id | doaj.art-ae8e5d65e31e42f58de4e50aa491c45f |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-11T20:35:35Z |
| publishDate | 2018-10-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-ae8e5d65e31e42f58de4e50aa491c45f2023-10-02T07:01:40ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-10-0136593394110.1051/jnwpu/20183650933jnwpu2018365p933Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF01234School of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversityAviation Ammunition Research Institute of Weapon Industry GroupSchool of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversityOptimal two stage Kalman filter (OTSKF) is able to obtain optimal estimation of system states and bias for linear system which contains random bias. Unscented Kalman filter (UKF) is a conventional nonlinear filtering method which utilizes Sigmas point sampling and unscented transformation technology realizes propagation of state means and covariances through nonlinear system. Aircraft is a typical complicate nonlinear system, this paper treats the faults of Inertial Measurement Unit (IMU) as random bias, established a filtering model which contains faults of IMU. Hybird the two stage filtering technique and UKF, this paper proposed an optimal two stage unscented Kalman filter (OTSUKF) algorithm which is suitable for fault diagnosis of IMU, realized optimal estimation of system states and faults identification of IMU via proposed innovative designing method of filtering model and the algorithm was validated that it is robust to wind disterbance via real flight data and it is also validated that proposed OTSUKF is optimal in the existance of wind disturbance via comparing with the existance iterated optimal two stage extended kalman filter (IOTSEKF) method.https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p933.pdfoptimal two stage unscented kalman filterrandom biasinertial measurement unitstate estimationfault diagnosis |
| spellingShingle | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF Xibei Gongye Daxue Xuebao optimal two stage unscented kalman filter random bias inertial measurement unit state estimation fault diagnosis |
| title | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF |
| title_full | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF |
| title_fullStr | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF |
| title_full_unstemmed | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF |
| title_short | Aircraft Inertial Measurement Unit Fault Diagnosis Based on Optimal Two-Stage UKF |
| title_sort | aircraft inertial measurement unit fault diagnosis based on optimal two stage ukf |
| topic | optimal two stage unscented kalman filter random bias inertial measurement unit state estimation fault diagnosis |
| url | https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p933.pdf |