Abstract

For over a decade, Brigham Young University's Microwave Earth Remote Sensing (MERS) team has been developing SAR systems and SAR processing algorithms. In order to create the most accurate image reconstruction algorithms, detailed aircraft motion data is essential. In 2008, the MERS team purchased a costly inertial measurement unit (IMU) coupled with a high precision global positioning system (GPS) from NovAtel, Inc. In order to lower the cost of obtaining detailed motion measurements, the MERS group decided to build a system that mimics the capability the NovAtel system as closely as possible for a much lower cost. As a first step, the same sensors and a simplified set of flight dynamics are used. This thesis presents a standalone motion sensor recording system (MOTRON), and outlines a method of utilizing the square-root Unscented Kalman filter (SR-UKF) to estimate aircraft flight dynamics, based on recorded flight data, as an alternative to the extended Kalman filter. While the results of the SR-UKF are not as precise as the NovAtel results, they approach the accuracy of the NovAtel system despite the simplified dynamics model.

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2009-10-02

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd3181

Keywords

SR-UKF, UKF, aircraft, flight, dynamics, Kalman, filter, GPS, accelerometer, gyroscope, airplane, tracking, SAR, motion, processing, sensor, IMU, MATLAB, roll, pitch, yaw, MOTRON, UAV, unscented

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