A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation
A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF) is used to provide a useful tool for combining in...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/6217428 |
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| author | Yu Gu Jason N. Gross Matthew B. Rhudy Kyle Lassak |
| author_facet | Yu Gu Jason N. Gross Matthew B. Rhudy Kyle Lassak |
| author_sort | Yu Gu |
| collection | DOAJ |
| description | A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF) is used to provide a useful tool for combining information from multiple sources. A two-step off-line and on-line calibration procedure refines sensor error models and improves the measurement performance. A Fault Detection and Identification (FDI) scheme crosschecks sensor measurements and simultaneously monitors sensor biases. Low-quality or faulty sensor readings are then rejected from the final sensor fusion process. The attitude estimation problem is used as a case study for the multiple sensor fusion algorithm design, with information provided by a set of low-cost rate gyroscopes, accelerometers, magnetometers, and a single-frequency GPS receiver’s position and velocity solution. Flight data collected with an Unmanned Aerial Vehicle (UAV) research test bed verifies the sensor fusion, adaptation, and fault-tolerance capabilities of the designed sensor fusion algorithm. |
| format | Article |
| id | doaj-art-2f26f728d8ef40ff98b77769aca72fbb |
| institution | OA Journals |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-2f26f728d8ef40ff98b77769aca72fbb2025-08-20T02:08:12ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742016-01-01201610.1155/2016/62174286217428A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude EstimationYu Gu0Jason N. Gross1Matthew B. Rhudy2Kyle Lassak3Department of Mechanical and Aerospace Engineering (MAE) at West Virginia University (WVU), Morgantown, WV 26506, USADepartment of Mechanical and Aerospace Engineering (MAE) at West Virginia University (WVU), Morgantown, WV 26506, USADivision of Engineering, Pennsylvania State University, Reading, PA 19610, USADepartment of Mechanical and Aerospace Engineering (MAE) at West Virginia University (WVU), Morgantown, WV 26506, USAA novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF) is used to provide a useful tool for combining information from multiple sources. A two-step off-line and on-line calibration procedure refines sensor error models and improves the measurement performance. A Fault Detection and Identification (FDI) scheme crosschecks sensor measurements and simultaneously monitors sensor biases. Low-quality or faulty sensor readings are then rejected from the final sensor fusion process. The attitude estimation problem is used as a case study for the multiple sensor fusion algorithm design, with information provided by a set of low-cost rate gyroscopes, accelerometers, magnetometers, and a single-frequency GPS receiver’s position and velocity solution. Flight data collected with an Unmanned Aerial Vehicle (UAV) research test bed verifies the sensor fusion, adaptation, and fault-tolerance capabilities of the designed sensor fusion algorithm.http://dx.doi.org/10.1155/2016/6217428 |
| spellingShingle | Yu Gu Jason N. Gross Matthew B. Rhudy Kyle Lassak A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation International Journal of Aerospace Engineering |
| title | A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation |
| title_full | A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation |
| title_fullStr | A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation |
| title_full_unstemmed | A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation |
| title_short | A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation |
| title_sort | fault tolerant multiple sensor fusion approach applied to uav attitude estimation |
| url | http://dx.doi.org/10.1155/2016/6217428 |
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