Navigation for UAVs using Signals of Opportunity
Issue Date
2015-12-31Author
Al Aziz, Masud
Publisher
University of Kansas
Format
137 pages
Type
Dissertation
Degree Level
Ph.D.
Discipline
Electrical Engineering & Computer Science
Rights
Copyright held by the author.
Metadata
Show full item recordAbstract
The reliance of Unmanned Aerial Vehicles (UAVs) on Global Navigation Satellite System (GNSS) for autonomous operation represents a significant vulnerability to their reliable and secure operation due to signal interference, both incidental (e.g. terrain shadowing, ionospheric scintillation) and malicious (e.g. jamming, spoofing). An accurate and reliable alternative UAV navigation system is proposed that exploits Signals of Opportunity (SOP) thus offering superior signal strength and spatial diversity compared to satellite signals. Given prior knowledge of the transmitter's position and signal characteristics, the proposed technique utilizes triangulation to estimate the receiver's position. Dual antenna interferometry provides the received signals' Angle of Arrival (AoA) required for triangulation. Reliance on precise knowledge of the antenna system's orientation is removed by combining AoAs from different transmitters to obtain a differential Angles of Arrival (dAoAs). Analysis, simulation, and ground-based experimental techniques are used to characterize system performance; a path to miniaturized system integration is also presented. Results from these ground-based experiments show that when the received signal-to-noise ratio (SNR) is above about 45 dB (typically in within 30 km of the transmitters), the proposed method estimates the receiver's position uncertainty range from less than 20 m to about 60 m with an update rate of 10 Hz.
Collections
- Dissertations [4626]
- Engineering Dissertations and Theses [1055]
Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.