Synthetic vision for Remotely Piloted Aircraft in non-segregated airspace

Synthetic Vision Systems (SVS) provide a computer-generated depiction of the environment according to aircraft flight path and attitude. In the case of Remotely-Piloted Aircraft (RPA), SVS improve dramatically operator situation awareness under reduced visibility conditions due to environment related issues and/or video data link degradation. Even though at their definition NextGen/SESAR frameworks were not thought to integrate RPA operations into non-segregated airspace, concepts such as flow corridors and technologies such as Traffic Information Service Broadcast will ease their incorporation. This paper proposes and assesses new concepts applied to SVS in order to increase RPA operator situation awareness taking advantage of new data sources that may be available in the future NextGen/SESAR frameworks. Based on raw telemetry data and accessible terrain databases, a SVS is built. The integration of trajectory data and air traffic information is designed and implemented in order to determine its benefits.