Author

Leah Tracy

Date of Award

2014

Document Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

Committee Chair

Laurie L. Joiner

Committee Member

Jeffrey Kulick

Committee Member

Merv Budge

Subject(s)

Kalman filtering, Inertial navigation systems, Global Positioning System

Abstract

A poor musical performance is rarely due to an inferior instrument. When a device is under performing, the temptation is to find a better device or a new technology to achieve performance objectives; however, another solution may be improving how existing technology is used through a better understanding of device characteristics, i.e., learning to play the instrument better. This thesis explores improving position and attitude estimates of inertial navigation systems (INS) through an understanding of inertial sensor errors, manipulating inertial measurement units (IMUs) to reduce that error and multisensor fusion of multiple IMUs to reduce error in a GPS denied environment.

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