Current Search: Ah-Chong, Jeremy Fred. (x)
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Title
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Static error modeling of sensors applicable to ocean systems.
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Creator
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Ah-Chong, Jeremy Fred., Florida Atlantic University, An, Edgar
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Abstract/Description
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This thesis presents a method for modeling navigation sensors used on ocean systems and particularly on Autonomous Underwater Vehicles (AUV). An extended Kalman filter was previously designed for the implementation of the Inertial Navigation System (INS) making use of Inertial Measurement Unit (IMU), a magnetic compass, a GPS/DGPS system and a Doppler Velocity Log (DVL). Emphasis is put on characterizing the static sensor error model. A "best-fit ARMA model" based on the Aikake Information...
Show moreThis thesis presents a method for modeling navigation sensors used on ocean systems and particularly on Autonomous Underwater Vehicles (AUV). An extended Kalman filter was previously designed for the implementation of the Inertial Navigation System (INS) making use of Inertial Measurement Unit (IMU), a magnetic compass, a GPS/DGPS system and a Doppler Velocity Log (DVL). Emphasis is put on characterizing the static sensor error model. A "best-fit ARMA model" based on the Aikake Information Criterion (AIC), Whiteness test and graphical analyses were used for the model identification. Model orders and parameters were successfully estimated for compass heading, GPS position and IMU static measurements. Static DVL measurements could not be collected and require another approach. The variability of the models between different measurement data sets suggests online error model estimation.
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Date Issued
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2003
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PURL
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http://purl.flvc.org/fcla/dt/12977
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Subject Headings
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Underwater navigation, Kalman filtering, Error-correcting codes (Information theory), Detectors
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Format
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Document (PDF)
