Wind Profile Estimation during Flight Path Reconstruction

  • T.K. Nusrath Khadeeja CSIR-National Aerospace Laboratories, Bengaluru - 560 017
  • Jatinder Singh CSIR-National Aerospace Laboratories, Bengaluru - 560 017
Keywords: Wind model, Flight path reconstruction, Flight data, Flow angles, Augmented state, State estimation, Extended Kalman filter


Accuracy of flow angles measurements becomes crucial as the aircraft approaches higher angle of attack. Flight path reconstruction (FPR) is an excellent tool for air data calibration. An important element of air data calibration is the estimation of wind velocities. The objective of this paper is to evaluate different approaches of wind estimation within the framework of FPR. Flight test data of a high performance aircraft is subjected to FPR and the estimated wind velocities and flow angle trajectories are presented and discussed to demonstrate the impact of wind estimation on aircraft flow angles. Results clearly show that accuracy of reconstructed flow angles improves when time varying wind models are used. The proposed analytical wind model is found to be as effective as augmented parameters in Extended Kalman filter and computationally less intensive.


Jategaonkar, R.V. Flight vehicle system identification: A time domain methodology. AIAA, Reston, VA, 2006. ISBN : 978-1-62410-278-3

Haering, E. A. Air data calibration of a high-performance aircraft for measuring atmospheric wind profiles. NASA TM-101714, 1990.

Chowdhary, Girish & Jategaonkar, Ravindra. Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter. Aerospace Sci. Technol., 2010, 14(2), 106–117.

Nusrath, K.; Sarmah, A. & Singh, J. Flight path reconstruction and wind estimation using flight test data from crash data recorder (CDR). SAE Technical Paper, 2014, 2014-01-2168.

Jared, A. Grauer. Real-time data-compatibility analysis using output-error parameter estimation. Journal Aircraft, 2015, 52(3), 940-947.

Teixeira, Soares; Torres, Leonardo; Henriques, Paulo; Oliveira, Iscold & Aguirre, Luis. Flight path reconstruction using the unscented Kalman filter algorithm. In 18th International Congress of Mechanical Engineering, Ouro Preto, MG, Nov. 6-11, 2005.

Parks, E.K.; Wingrove, R.C.; Bach, R.E. Jr. & Mehta, R.S. Identification of vortex-induced clear-air turbulence using airline flight records. Journal Aircraft, 1985, 22(2), 124-129.

Lewis, G. Using GPS to determine pitot-static errors. National Test Pilot School, Mojave, California, 2003.

Meir, Pachter.; Nicola, Ceccarelli & Phillip, R. Chandler. Estimating MAV’s heading and the wind speed and direction using GPS, inertial, and air speed measurements. In Proceedings of AIAA Guidance, Navigation & Control conference and exhibit, Hawaii, 2008-6311.

Mulgund, Sandeep S. & Robert, F. Stengels. Optimal nonlinear estimation for aircraft flight control in wind shear. Automatica, 1996, 32(1), 3-13.

Gratton, G. B. Use of Global Positioning system velocity outputs for determining airspeed measurement error. The Aeronautical Journal, 2007, 111(1120), 381-388.

Bach, R.E. & Wingrove, R.C. Analysis of wind shear from airline flight data. AIAA Journal Aircraft, 1989, 26(2), 103-109.

Bach, R.E. Jr. & Parks, E.K. Angle-of-Attack estimation for analysis of windshear encounters. AIAA Journal Aircraft, 1987, 24(11), 789-792.

Brian, R. Taylor. A Full-Envelope Air data calibration and three-dimensional wind estimation method using global output-error optimization and flight-test techniques. In AIAA Conference, August 2012.

De Jong, P. M. A.; van der Laan, J. J.; int Veld, A.C.; van Paassen, M. M. & Mulder, M. Wind-profile estimation using airborne sensors. AIAA Journal Aircraft, 2014, 51(6).

Cho, A.M.; Jihoon, Kim; Sanghyo, Lee & Changdon, Kee. Wind estimation and airspeed calibration using a UAV with a single-antenna gps receiver and pitot tube. IEEE Trans. Aerospace Electron. Syst., 2011, 47(1), 109-117. TAES. 2011. 5705663

Lee, Je Hyeon; Hakki, Erhan Sevil; Atilla, Dogan & David, Hullender. Estimation of maneuvering aircraft states and time varying wind with turbulence. Aerospace Sci. Technol., 2013, 31(1), 87–98.

Madapusi, H.J. Palanthandalam; Girard, A. & Bernstein, D.S. Wind field reconstruction using flight data. In Proceedings of the American Control Conference, Seattle, WA, 2008, 1863–1868.

Kamali, C. & Erol, Ozger. Limitations of flight path reconstruction techniques, Sadhana, 2019, 44(2), 1-15.

Wingrove, R.C. & Bach, R.E. Severe winds in the DFW microburst measured from two aircraft. J. Aircraft, 1989, 26(3), 221-224.

Ching Yaw Tzeng. Wind shear estimation along the trajectory of an aircraft. Rice University, Texas, 1989. (PhD Thesis).

How to Cite
Khadeeja, T., & Singh, J. (2020). Wind Profile Estimation during Flight Path Reconstruction. Defence Science Journal, 70(3), 231-239.
Aeronautical Systems