DocumentCode
2913862
Title
Aircraft local wind estimation from radar tracker data
Author
Delahaye, Daniel ; Puechmorel, Stéphane
Author_Institution
French Civil Aviation Sch., Toulouse
fYear
2008
fDate
17-20 Dec. 2008
Firstpage
1033
Lastpage
1038
Abstract
Accurate wind magnitude and direction estimation is essential for aircraft trajectory prediction. For instance, based on these data, one may compute entry and exit times from a sector or detect potential conflict between aircraft. Since the flight path has to be computed and updated on real time for such applications, wind information has to be available in real time too.The wind data which are currently available through meteorological service broadcast suffer from small measurement rate with respect to location and time. In this paper, a new wind estimation method based on radar track measures is proposed. When on board true air speed measures are available, a linear model is developed for which a Kalman filter is used to produce high quality wind estimate. When only aircraft position measures are available, an observability analysis shows that wind may be estimated only if trajectories have one or two turns depending of the number of aircraft located in a given area. Based on this observability conditions, closed forms of the wind has been developed for the one and two aircraft cases. By this mean, each aircraft can be seen as a wind sensor when it is turning. After performing evaluations in realistic frameworks, our approach is able to estimate the wind vectors accurately.
Keywords
Kalman filters; aircraft; meteorological radar; prediction theory; velocity measurement; wind; Kalman filter; air speed measurement; aircraft local wind estimation; aircraft trajectory prediction; linear model; meteorological service broadcast; observability analysis; radar tracking; wind direction estimation; wind magnitude estimation; Airborne radar; Aircraft; Broadcasting; Current measurement; Meteorology; Observability; Radar detection; Radar tracking; Trajectory; Wind forecasting; Air traffic management; Kalman filter; Speed triangle; Trajectory prediction; Wind estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
Conference_Location
Hanoi
Print_ISBN
978-1-4244-2286-9
Electronic_ISBN
978-1-4244-2287-6
Type
conf
DOI
10.1109/ICARCV.2008.4795661
Filename
4795661
Link To Document