NTRS - NASA Technical Reports Server

Back to Results
Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and WindManaging trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.
Document ID
Acquisition Source
Ames Research Center
Document Type
Conference Paper
D'Souza, Sarah
(NASA Ames Research Center Moffett Field, CA, United States)
Ishihara, Abraham K.
(SGT, Inc. Moffett Field, CA, United States)
Nikaido, Ben Edward
(Science and Technology Corp. Moffett Field, CA, United States)
Hasseeb, Hashmatullah
(Science and Technology Corp. Moffett Field, CA, United States)
Date Acquired
December 26, 2018
Publication Date
September 25, 2016
Subject Category
Air Transportation And Safety
Report/Patent Number
Meeting Information
Meeting: Digital Avionics Systems Conference 2016
Location: Sacramento, CA
Country: United States
Start Date: September 25, 2016
End Date: September 29, 2016
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
Distribution Limits
Public Use Permitted.
trajecory prediction
No Preview Available