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.
Worcester Polytechnic Institute
Electrical and Computer Engineering
Major Qualifying Project
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