Student: Teisha D. Hall
Senior Researcher: Dr. Scott
Title: Refinement of Data Conversion Processes for Synthetic Vision Systems
The need for improved safety in air traffic has increased because the Flight Safety Foundation has predicted that air traffic is expected to double over the next decade. NASA’s Aviation Safety Program has proposed to develop a Synthetic Vision System that will provide pilots with improved situational awareness. A synthetic vision system is a database derived system which utilizes precise Global Positioning System navigation and integrity-monitoring sensors to provide an unrestricted synthetic view of the aircrafts current external environment. With the aid of a SVS pilots will be equipped with an unobstructed view of terrain regardless of weather and, or time of day which will enhance situational awareness. The SVS will eventually be used in military, commercial and general aviation aircrafts. The Project hopes to help NASA drastically reduce the number of Aviation accidents caused by Controlled Flight into Terrain (CFT, when the Pilot miscalculates his position and has an accident) and low visibility, thereby reducing the stress on the pilot and increasing his/her performance. The stored geo-spatial data is available in the form of DEM (Digital Elevation Model) files, which must be rendered in order for them to be readable by a pilot. The output after rendering is a mathematical approximation of the actual terrain. Current SVS uses a polygonal rendering method that is not efficient at producing a precise image, and requires pre-compiling of the DEM file. This project will explore the point cloud rendering technique, at the present time no other SVS has incorporated this rendering technique. This method of rendering has produced more precise 3-dimensional images, but is just as fast as the other options available and does not require pre-compiling the DEM file.
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