An application of Extended Kalman filtering to a model-based, short-range navigator for an AUV.
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Authors
Miller, Christopher A.
Subjects
AUV
Extended Kalman Filter
Nonlinear Systems
Linearization
Navigation
Extended Kalman Filter
Nonlinear Systems
Linearization
Navigation
Advisors
Cristi, Roberto
Date of Issue
1991-12
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Autonomous Underwater Vehicles (AUV) are being
considered by the Navy for performing a variety of missions.
During the research and development stage of the AUV project
at the Naval Postgraduate School, a navigator is needed to
provide vehicle position estimates for short-range missions
performed in a test pool environment. This navigator should
operate with inexpensive sensors and not require excessive
digital processor time. This thesis presents the results of
the design of a model-based navigator. The navigator uses
nonlinear vehicle models and Extended Kalman filter theory.
Simulation studies for both a 12,000 pound vehicle and the
435 pound testbed vehicle, designed and built at the School
(NPS AUV II), are presented. Results of using data recorded
from the gyroscopes and depth cell installed in the NPS AUV II vehicle in lieu of simulated data are also discussed.
These results show that the navigator meets the goals of low
cost and low processor burden for short-range missions.
Type
Thesis
Description
Series/Report No
Department
Electrical Engineering
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
150 p.;28 cm.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.