Kalman filtering for aided inertial navigation system
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2005
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| Online Access: | http://hdl.handle.net/1721.1/9380 |
| _version_ | 1826205855390892032 |
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| author | Korka, David A. (David Andrew), 1976- |
| author2 | Jamie Anderson. |
| author_facet | Jamie Anderson. Korka, David A. (David Andrew), 1976- |
| author_sort | Korka, David A. (David Andrew), 1976- |
| collection | MIT |
| description | Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999. |
| first_indexed | 2024-09-23T13:20:10Z |
| format | Thesis |
| id | mit-1721.1/9380 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:20:10Z |
| publishDate | 2005 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/93802019-04-12T17:24:07Z Kalman filtering for aided inertial navigation system Korka, David A. (David Andrew), 1976- Jamie Anderson. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999. Includes bibliographical references (p. 65). This thesis develops a Kalman filter which integrates the inertial navigation system of the Vorticity Control Unmanned Undersea Vehicle (VCUUV) with redundant navigation sensor measurements. The model for the Kalman filter uses redundant measurements in a feedback loop to better estimate navigation variables. Using outputs from the Inertial Measurement Unit (IMU) and from a depth sensor, a velocity sensor and a magnetometer, a Kalman filter is developed. Actual test runs on the VCUUV prove the new system superior to the previously used open-loop navigation system. by David A. Korka. S.B.and M.Eng. 2005-08-22T20:44:24Z 2005-08-22T20:44:24Z 1999 1999 Thesis http://hdl.handle.net/1721.1/9380 44878364 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 69 p. 3989324 bytes 3989084 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Korka, David A. (David Andrew), 1976- Kalman filtering for aided inertial navigation system |
| title | Kalman filtering for aided inertial navigation system |
| title_full | Kalman filtering for aided inertial navigation system |
| title_fullStr | Kalman filtering for aided inertial navigation system |
| title_full_unstemmed | Kalman filtering for aided inertial navigation system |
| title_short | Kalman filtering for aided inertial navigation system |
| title_sort | kalman filtering for aided inertial navigation system |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/9380 |
| work_keys_str_mv | AT korkadavidadavidandrew1976 kalmanfilteringforaidedinertialnavigationsystem |