Unmanned Aerial Vehicles continue to pose an immediate threat to personal privacy and national security. In an effort to detect the threat of unwanted drones, our team designed a RSS-Based 3D localization system utilizing software-defined radio. This report focused on localization of hobbyist drones by detecting and quantifying the received signal strength of the video stream emitted by the drone to the remote controller. The adaptive filtering algorithm, recursive least squares, was used to numerically estimate the drone's 3D position. The precision and accuracy of our system was quantified by distance measurement error, as well as the Cramer-Rao lower bound.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Loftus, John Patrick
• Gelman, Ian Solomon
• Hassan, Abdul Ali

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-041719-144214

Advisor

• Pahlavan, Kaveh

Year

• 2019

Date created

• 2019-04-17

Resource type

• Major Qualifying Project

Major

• Electrical & Computer Engineering

Rights statement

• In Copyright

License

• All rights reserved