DocumentCode
184751
Title
Wind field estimation in UAV formation flight
Author
Larrabee, Trenton ; Haiyang Chao ; Rhudy, Matthew ; Yu Gu ; Napolitano, Marcello R.
Author_Institution
MAE Dept., West Virginia Univ., Morgantown, WV, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
5408
Lastpage
5413
Abstract
Wind and turbulence, including wakes induced by leading aircraft, have a large impact on flight performance and flight safety of both manned and unmanned aircraft. An accurate real-time wind estimation technique is crucial for tasks such as increasing air traffic capacity, commercial formation flight, or aerial refueling, etc. A leader-follower formation flight of Phastball Unmanned Aerial Vehicles (UAVs) were used as the experimental platform for the above problem. The air data system of Phastball UAV was developed with pitot-tube and flow-angle sensors. Using the designed system, two Unscented Kalman Filters (one standalone UKF and one cooperative UKF) were developed for the wind field estimation with and without using the wake information from the leader aircraft. For close formation flights, the wake of the leader is assumed to be predictable by certain wake models for the follower aircraft. Flight data showed the effectiveness of the standalone EKF for the wind estimation compared with the ground weather station measurements. Simulation results showed the advantage of the cooperative UKF over the standalone UKF.
Keywords
Kalman filters; aerospace safety; autonomous aerial vehicles; nonlinear filters; sensors; turbulence; wakes; wind; Phastball unmanned aerial vehicles; UAV formation flight; air data system; cooperative UKF; flight performance; flight safety; flow-angle sensors; ground weather station measurements; leader-follower formation flight; manned aircraft; pitot-tube; standalone UKF; turbulence; unmanned aircraft; unscented Kalman filters; wake information; wind field estimation; Aircraft; Atmospheric modeling; Estimation; Global Positioning System; Mathematical model; Sensors; Wind; Air Data System; Formation Flight; Wake Modeling; Wind Estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6859266
Filename
6859266
Link To Document