Date Approved

11-24-2023

Embargo Period

11-27-2023

Document Type

Thesis

Degree Name

Master of Science (M.S.)

Department

Electrical and Computer Engineering

College

Henry M. Rowan College of Engineering

Advisor

Nidhal Bouaynaya, Ph.D.

Committee Member 1

Ravi Ramachandran, Ph.D.

Committee Member 2

Mike Paglione

Keywords

Conflicts; Detect and Avoid; Simulations; Unmanned Aircraft Systems

Subject(s)

Drone aircraft--Control systems

Disciplines

Aerospace Engineering | Computer Engineering | Engineering

Abstract

There is ongoing research at the Federal Aviation Administration (FAA) and other private industries to examine a concept for delegated separation in multiple classes of airspace to allow unmanned aircraft systems (UAS) to remain well clear of other aircraft. Detect and Avoid (DAA) capabilities are one potential technology being examined to maintain separation. To evaluate these DAA capabilities, input traffic scenarios are needed, but current approaches are limited by the breadth of the traffic recordings available. This thesis derives a new mathematical algorithm that uses great circle navigation equations in an Earth spherical model and an accurate aircraft performance model to generate realistic aircraft encounters in any airspace. This algorithm is implemented in a program called Encounters from Actual Trajectories (EnAcT) and uses several user inputs defining the encounter events, called encounter properties. Given these encounter properties, the program generates two 4-dimensional flight trajectories that satisfy these properties. This thesis also describes a study performed to determine the appropriate encounter properties to use for developing the encounters. This encounter generator could be used to evaluate DAA systems as well as initiate research in automation for encounter detection and resolution.

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