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Kalman filtering for aided inertial navigation system

Author(s)
Korka, David A. (David Andrew), 1976-
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Jamie Anderson.
Terms of use
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
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Abstract
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.
Description
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
 
Includes bibliographical references (p. 65).
 
Date issued
1999
URI
http://hdl.handle.net/1721.1/9380
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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