Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2006
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| Online Access: | http://hdl.handle.net/1721.1/34136 |
| _version_ | 1826190244977836032 |
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| author | Thompson, Gordon A. (Gordon Alexander) |
| author2 | Steven R. Hall and J. Arnold Soltz. |
| author_facet | Steven R. Hall and J. Arnold Soltz. Thompson, Gordon A. (Gordon Alexander) |
| author_sort | Thompson, Gordon A. (Gordon Alexander) |
| collection | MIT |
| description | Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005. |
| first_indexed | 2024-09-23T08:37:17Z |
| format | Thesis |
| id | mit-1721.1/34136 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:37:17Z |
| publishDate | 2006 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/341362019-04-09T18:49:55Z Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering IMU calibration using FIMLOF Thompson, Gordon A. (Gordon Alexander) Steven R. Hall and J. Arnold Soltz. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005. Includes bibliographical references (p. 105-108). The robustness of Full Information Maximum Likelihood Optimal Filtering (FIMLOF) for inertial measurement unit (IMU) calibration in high-g centrifuge environments is considered. FIMLOF uses an approximate Newton's Method to identify Kalman Filter parameters such as process and measurement noise intensities. Normally, IMU process noise intensities and measurement standard deviations are determined by laboratory testing in a 1-g field. In this thesis, they are identified along with the calibration of the IMU during centrifuge testing. The partial derivatives of the Kalman Filter equations necessary to identify these parameters are developed. Using synthetic measurements, the sensitivity of FIMLOF to initial parameter estimates and filter suboptimality is investigated. The filter residuals, the FIMLOF parameters, and their associated statistics are examined. The results show that FIMLOF can be very successful at tuning suboptimal filter models. For systems with significant mismodeling, FIMLOF can substantially improve the IMU calibration and subsequent navigation performance. In addition, FIMLOF can be used to detect mismodeling in a system, through disparities between the laboratory-derived parameter estimates and the FIMLOF parameter estimates. by Gordon A. Thompson. S.M. 2006-09-28T15:06:37Z 2006-09-28T15:06:37Z 2005 2005 Thesis http://hdl.handle.net/1721.1/34136 67770625 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 108 p. 4930210 bytes 4934684 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Aeronautics and Astronautics. Thompson, Gordon A. (Gordon Alexander) Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title | Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title_full | Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title_fullStr | Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title_full_unstemmed | Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title_short | Inertial measurement unit calibration using Full Information Maximum Likelihood Optimal Filtering |
| title_sort | inertial measurement unit calibration using full information maximum likelihood optimal filtering |
| topic | Aeronautics and Astronautics. |
| url | http://hdl.handle.net/1721.1/34136 |
| work_keys_str_mv | AT thompsongordonagordonalexander inertialmeasurementunitcalibrationusingfullinformationmaximumlikelihoodoptimalfiltering AT thompsongordonagordonalexander imucalibrationusingfimlof |