Date of Award
Spring 2015
Degree Type
Thesis
Degree Name
Master of Science in Aeronautics and Astronautics
Department
Aeronautics and Astronautics
First Advisor
Inseok Hwang
Committee Chair
Inseok Hwang
Committee Member 1
Dengfeng Sun
Committee Member 2
Daniel DeLaurentis
Abstract
Navigation for the autonomous flight of Unmanned Aerial Vehicles (UAVs) in an indoor space has attracted much attention recently. One of the main goals of an indoor navigation system is developing an alternative method to obtain position information that can replace or complement the global positioning system. While much research has focused on vision-based indoor navigation systems, this paper aims to develop a Received Signal Strength (RSS)-based navigation system, which is a more cost effective alternative. Then, the position and attitude of a UAV can be computed by the fusion of RSS measurements and measurements from the onboard inertial measurement unit. In order to improve the estimation accuracy, we first consider a mathematical model of the RSS-based navigation system and formulate optimization problems to compute the parameter values which minimize the RSS measurement error. Using the optimal parameters, an autonomous flight system is developed whose estimator and controller components are designed to work well with the RSS-based navigation system. Simulations and experiments using a quadrotor demonstrate the feasibility and performance of the proposed RSS-based navigation system for UAVs operating in indoor environments.
Recommended Citation
Lee, Sangjun, "Real-time rss-based indoor navigation for autonomous UAV flight" (2015). Open Access Theses. 478.
https://docs.lib.purdue.edu/open_access_theses/478