Date of Award

3-26-2015

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Brian G. Woolley, PhD.

Abstract

The ubiquitous nature of GPS has fostered its widespread integration of navigation into a variety of applications, both civilian and military. One alternative to ensure continued flight operations in GPS-denied environments is vision-aided navigation, an approach that combines visual cues from a camera with an inertial measurement unit (IMU) to estimate the navigation states of a moving body. The majority of vision-based navigation research has been conducted in the electro-optical (EO) spectrum, which experiences limited operation in certain environments. The aim of this work is to explore how such approaches extend to infrared imaging sensors. In particular, it examines the ability of medium-wave infrared (MWIR) imagery, which is capable of operating at night and with increased vision through smoke, to expand the breadth of operations that can be supported by vision-aided navigation. The experiments presented here are based on the Minor Area Motion Imagery (MAMI) dataset that recorded GPS data, inertial measurements, EO imagery, and MWIR imagery captured during flights over Wright-Patterson Air Force Base. The approach applied here combines inertial measurements with EO position estimates from the structure from motion (SfM) algorithm. Although precision timing was not available for the MWIR imagery, the EO-based results of the scene demonstrate that trajectory estimates from SfM offer a significant increase in navigation accuracy when combined with inertial data over using an IMU alone. Results also demonstrated that MWIR-based positions solutions provide a similar trajectory reconstruction to EO-based solutions for the same scenes. While the MWIR imagery and the IMU could not be combined directly, through comparison to the combined solution using EO data the conclusion here is that MWIR imagery (with its unique phenomenologies) is capable of expanding the operating envelope of vision-aided navigation.

AFIT Designator

AFIT-ENG-MS-15-M-063

DTIC Accession Number

ADA620258

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