Attitude Determination Using a MEMS-Based Flight Information Measurement Unit
Obtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/1/1/ |
| _version_ | 1797999622354894848 |
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| author | Yu-Heng Lin I.-Chiang Wang Der-Ming Ma Jaw-Kuen Shiau |
| author_facet | Yu-Heng Lin I.-Chiang Wang Der-Ming Ma Jaw-Kuen Shiau |
| author_sort | Yu-Heng Lin |
| collection | DOAJ |
| description | Obtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to integrate the traditional quaternion and gravitational force decomposition methods for attitude determination algorithm. The proposed extended Kalman filter utilizes the evolution of the four elements in the quaternion method for attitude determination as the dynamic model, with the four elements as the states of the filter. The attitude angles obtained from the gravity computations and from the electronic magnetic sensors are regarded as the measurement of the filter. The immeasurable gravity accelerations are deduced from the outputs of the three axes accelerometers, the relative accelerations, and the accelerations due to body rotation. The constraint of the four elements of the quaternion method is treated as a perfect measurement and is integrated into the filter computation. Approximations of the time-varying noise variances of the measured signals are discussed and presented with details through Taylor series expansions. The algorithm is intuitive, easy to implement, and reliable for long-term high dynamic maneuvers. Moreover, a set of flight test data is utilized to demonstrate the success and practicality of the proposed algorithm and the filter design. |
| first_indexed | 2024-04-11T11:06:33Z |
| format | Article |
| id | doaj.art-9796971ed6e248c08a6bcd31e16d7a3c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:06:33Z |
| publishDate | 2011-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9796971ed6e248c08a6bcd31e16d7a3c2022-12-22T04:28:16ZengMDPI AGSensors1424-82202011-12-0112112310.3390/s120100001Attitude Determination Using a MEMS-Based Flight Information Measurement UnitYu-Heng LinI.-Chiang WangDer-Ming MaJaw-Kuen ShiauObtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to integrate the traditional quaternion and gravitational force decomposition methods for attitude determination algorithm. The proposed extended Kalman filter utilizes the evolution of the four elements in the quaternion method for attitude determination as the dynamic model, with the four elements as the states of the filter. The attitude angles obtained from the gravity computations and from the electronic magnetic sensors are regarded as the measurement of the filter. The immeasurable gravity accelerations are deduced from the outputs of the three axes accelerometers, the relative accelerations, and the accelerations due to body rotation. The constraint of the four elements of the quaternion method is treated as a perfect measurement and is integrated into the filter computation. Approximations of the time-varying noise variances of the measured signals are discussed and presented with details through Taylor series expansions. The algorithm is intuitive, easy to implement, and reliable for long-term high dynamic maneuvers. Moreover, a set of flight test data is utilized to demonstrate the success and practicality of the proposed algorithm and the filter design.http://www.mdpi.com/1424-8220/12/1/1/attitude determinationquaternionflight information measurement unitextended Kalman filter |
| spellingShingle | Yu-Heng Lin I.-Chiang Wang Der-Ming Ma Jaw-Kuen Shiau Attitude Determination Using a MEMS-Based Flight Information Measurement Unit Sensors attitude determination quaternion flight information measurement unit extended Kalman filter |
| title | Attitude Determination Using a MEMS-Based Flight Information Measurement Unit |
| title_full | Attitude Determination Using a MEMS-Based Flight Information Measurement Unit |
| title_fullStr | Attitude Determination Using a MEMS-Based Flight Information Measurement Unit |
| title_full_unstemmed | Attitude Determination Using a MEMS-Based Flight Information Measurement Unit |
| title_short | Attitude Determination Using a MEMS-Based Flight Information Measurement Unit |
| title_sort | attitude determination using a mems based flight information measurement unit |
| topic | attitude determination quaternion flight information measurement unit extended Kalman filter |
| url | http://www.mdpi.com/1424-8220/12/1/1/ |
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