Ryan Watson

Date of Graduation

2017

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Jason N Gross

Committee Co-Chair

John A Christian

Committee Member

Yu Gu

Abstract

UAVs have the potential for autonomous airborne remote sensing applications that require rapid response to natural hazards (e.g. volcano eruptions, earthquakes). As these applications require very accurate positioning, tightly coupled Global Positioning System (GPS) Precise Point Positioning (PPP) Inertial Navigation Systems (INS) are an attractive method to perform real-time aircraft positioning. In particular, PPP can achieve a level of positioning accuracy that is similar to Real-Time Kinematic (RTK) GPS, without the need of a relatively close GPS reference station. However, the PPP method is known to converge to accurate positioning estimate more slowly when compared to RTK, a drawback of PPP that is amplified whenever the receiver platform is faced with GPS challenged environments, such as poor satellite visibility and frequent phase breaks.;This thesis presents the use of a simulation environment that characterizes the position estimation performance sensitivity of PPP/INS through a Monte Carlo analysis that is considered under various conditions: such as, the intensity of multipath errors, the number of phase breaks, the satellite geometry, the atmospheric conditions, the noise characteristics of the inertial sensor, and the accuracy of GPS orbit products. After the PPP/INS formulation was verified in a simulation environment, the INS formulation was incorporated into NASA JPL's Real-Time GIPSY-x. This software was then verified using eight recorded flight data sets provided by the National Geodetic Survey (NGS), National Oceanic and Atmospheric Administration (NOAA) program called Gravity for the Redefinition of the American Vertical Datum (GRAV-D).

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