SUAS Flight Path Visualization

Small, uncrewed aircraft, systems, and drones can provide small military units with valuable intelligence, surveillance, and reconnaissance information. However, the flight paths of these drones must consider several factors to successfully gather the needed information while minimizing the chances of being detected. These factors may include models of the drone’s noise and visibility signatures, models of human vision and auditory perception, environmental factors, and models of drone sensors, among others.

The objective of this project is to develop, test, and deploy a 3D visualization architecture that will enable operators in small military units to plan, visualize, and modify drone flight paths over a given terrain to meet the mission success criteria of minimizing detection while making effective use of sensors over an area. With the OTA (Over-The-Air) updates provided by this web-based platform, future developers will have no trouble integrating and updating sensors, human perception, drone noise, and visibility models.

Student Team
  • Alex Alcazar
  • Francisco Brito
  • Helen Dam
  • Alex Gaeta
  • Alberto Gonzalez
  • Sergio Maradiaga Olivera
  • Thad Owens
  • Mychal Salgado
  • Kevin Tang
  • Sergio Valadez Polanco
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