GNSS/INS based estimation of air data and wind vector using flight maneuvers

Kerry Sun; Christopher D. Regan; Demoz Gebre Egziabher

doi:10.1109/PLANS.2018.8373461

GNSS/INS based estimation of air data and wind vector using flight maneuvers

Kerry Sun
, Christopher D. Regan
, Demoz Gebre Egziabher

Aerospace Engineering and Mechanics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Scopus citations

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.

Original language	English (US)
Title of host publication	2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	838-849
Number of pages	12
ISBN (Electronic)	9781538616475
DOIs	https://doi.org/10.1109/PLANS.2018.8373461
State	Published - Jun 5 2018
Event	2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Monterey, United States Duration: Apr 23 2018 → Apr 26 2018

Publication series

Name	2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings

Other

Other	2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018
Country/Territory	United States
City	Monterey
Period	4/23/18 → 4/26/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Flight Maneuverability
Kalman Filter Estimation
Observability
Synthetic Air Data

Publisher link

10.1109/PLANS.2018.8373461

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Sun, K., Regan, C. D., & Egziabher, D. G. (2018). GNSS/INS based estimation of air data and wind vector using flight maneuvers. In 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings (pp. 838-849). (2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PLANS.2018.8373461

GNSS/INS based estimation of air data and wind vector using flight maneuvers. / Sun, Kerry; Regan, Christopher D.; Egziabher, Demoz Gebre.
2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 838-849 (2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sun, K, Regan, CD & Egziabher, DG 2018, GNSS/INS based estimation of air data and wind vector using flight maneuvers. in 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings. 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 838-849, 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018, Monterey, United States, 4/23/18. https://doi.org/10.1109/PLANS.2018.8373461

Sun K, Regan CD, Egziabher DG. GNSS/INS based estimation of air data and wind vector using flight maneuvers. In 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 838-849. (2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings). doi: 10.1109/PLANS.2018.8373461

Sun, Kerry ; Regan, Christopher D. ; Egziabher, Demoz Gebre. / GNSS/INS based estimation of air data and wind vector using flight maneuvers. 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 838-849 (2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings).

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title = "GNSS/INS based estimation of air data and wind vector using flight maneuvers",

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.",

keywords = "Flight Maneuverability, Kalman Filter Estimation, Observability, Synthetic Air Data",

author = "Kerry Sun and Regan, \{Christopher D.\} and Egziabher, \{Demoz Gebre\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 ; Conference date: 23-04-2018 Through 26-04-2018",

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N2 - 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.

AB - 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.

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KW - Kalman Filter Estimation

KW - Observability

KW - Synthetic Air Data

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GNSS/INS based estimation of air data and wind vector using flight maneuvers

Abstract

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Keywords

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