Faculty Advisor

Pahlavan, Kaveh

Abstract

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.

Publisher

Worcester Polytechnic Institute

Date Accepted

April 2019

Major

Electrical and Computer Engineering

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Share

COinS