Title: GNSS/INS Based Estimation of Air Data and Wind Vector using Flight Maneuvers
Author(s): Kerry Sun, Christopher D. Regan, Demoz Gebre Egziabher
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 838 - 849
Cite this article: Sun, Kerry, Regan, Christopher D., Egziabher, Demoz Gebre, "GNSS/INS Based Estimation of Air Data and Wind Vector using Flight Maneuvers," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 838-849.
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Abstract: We develop a GNSS/INS based algorithm to estimate air data (angle-of-attack and sideslip angle) and wind vector in real time. Our work uses observability analysis to demonstrate the feasibility of the model-free synthetic air data estimation. In addition, we show that certain canonical flight maneuvers, defined by the aircraft’s orientation and airspeed, result in a high degree of observability for the air data parameters and the wind velocity vector estimates. Furthermore, a lower bound on the average time of wind variation can be derived from the analysis. Finally, the GNSS/INS-based algorithm is tested to estimate these parameters using simulation data. Results of simulation are consistent with the observability analysis.