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

12 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

Funding Information:
The authors would like to thank NASA (via Grant NNX15AV67G), UMN OVPR MnDRIVE Initiative, Sentera LLC. and LMCCR Legislature of the State of Minnesota for supporting this work. This work was part of the ongoing project called ”A Rapid Autonomy Platform Testbed Reconfiguration Suite” (RAPTRS) sponsored by NASA Ames Research Center.

Publisher Copyright:
© 2018 IEEE.

Keywords

Flight Maneuverability
Kalman Filter Estimation
Observability
Synthetic Air Data

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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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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.",

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

Abstract

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Keywords

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