This paper describes a method for estimating the relative pose of a pair of unmanned aerial vehicles (UAV) using noisy measurements from ranging radios and each aircraft's on board navigation system. In this method, there is no prior information needed about the relative pose of each UAV. During the estimation of the relative pose of two traveling UAVs, only a single range measurement between UAVs is needed at each location. To augment this limited information, motion is used to construct a graph with the range measurements and displacement in position over multiple locations. First, the analytical solution is derived for the pose from the constructed graph assuming the system is free of noise. Then, the relative heading and bearing are estimated from noisy range measurements and the displacement in position using nonlinear least squares. The sensitivity to the geometry and measurement noise are then analyzed for various trajectories. For this paper, the problem is analyzed for the twodimensional case where the UAVs are traveling at equal altitudes.

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In support of NASA's Unmanned Aircraft Systems Integration in the National Airspace System project and RTCA Special Committee 228, an analysis has been performed to provide insight in to the trade space between unmanned aircraft speed and turn capability and detect and avoid sensor range requirements. The work was done as an initial part of the effort to understand low size, weight, and power sensor requirements for aircraft that have a limited speed envelope or can limit the envelope for portions of their mission and may be able to turn at higher than "standard rate." Range and timeline reductions coming from limiting speed range and from increasing available turn rate in some speed ranges are shown.

Sensitivity Analysis of a Relative Navigation Solution for Unmanned Aerial Vehicles in a GNSS-denied Environment Jeremy Hardy 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 triaxial magnetometers, and downward facing cameras. Through the use of a Monte Carlo simulation study, the presented algorithm's 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.