Date of Award

1-1-2019

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering

First Advisor

Matthew J. Rutherford, Ph.D.

Second Advisor

Kimon P. Valavanis, Ph.D.

Keywords

Micro doppler, Radar, Sense and avoid, Software defined radar, Software defined radio, Unmanned aerial systems, UAS

Abstract

Advances in Unmanned Aerial Vehicle (UAV) technology have enabled wider access for the general public leading to more stringent flight regulations, such as the "line of sight" restriction, for hobbyists and commercial applications. Improving sensor technology for Sense And Avoid (SAA) systems is currently a major research area in the unmanned vehicle community. This thesis overviews efforts made to advance intelligent algorithms used to detect, track, and identify commercial UAV targets by enabling rapid prototyping of novel radar techniques such as micro-Doppler radar target identification or cognitive radar. To enable empirical radar signal processing evaluations, an S-Band and X-Band frequency modulated, software-defined radar testbed is designed, implemented, and evaluated with field measurements. The final evaluations provide proof of functionality, performance measurements, and limitations of this testbed and future software-defined radars. The testbed is comprised of open-source software and hardware meant to accelerate the development of a reliable, repeatable, and scalable SAA system for the wide range of new and existing UAVs.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Erik George Moore

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

211 p.

Discipline

Electrical engineering, Aerospace engineering, Electromagnetics

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