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 :
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