Sensitivity analysis of a relative navigation solution for unmanned aerial vehicles in a GNSS-denied environment

Abstract

Cooperative navigation between two or more unmanned aerial vehicles (UAVs) is an important enabling technology for problems such as military reconnaissance, disaster response, and search and rescue. In many of these situations Global Navigation Satellite Systems (GNSS), such as Global Positioning System (GPS), may be unreliable or unavailable due to structural impedance or malicious signal jamming. Therefore, the task of maintaining a reliable relative navigation solution without the use of GNSS is an important need for the aforementioned missions.;To meet this need, this thesis focuses on the relative navigation between two UAVs that are operating in a GNSS-denied environment. In particular, the design and sensitivity of a navigation algorithm are presented. The navigation algorithm presented consists of an Unscented Kalman filter that fuses multiple on-board sensors to estimate the relative pose between two UAVs. These sensors include: strap-down inertial measurement units, ultra-wideband ranging radios, strap-down tri-axial magnetometers, and downward facing cameras. Through the use of a Monte Carlo simulation study, the presented algorithm\u27s performance sensitivity to various sensor payload characteristics, flight dynamics, and initial condition errors is evaluated. Additionally, a research platform that will provide for a future experimental evaluation of the algorithm presented in this thesis has been integrated and tested as part of this work