Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements

Chingiz Hajiyev; Demet Cilden-Guler; Ulviye Hacizade

doi:10.1109/RAST.2019.8767886

Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements

Chingiz Hajiyev, Demet Cilden-Guler, Ulviye Hacizade

Halic University

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

8 Citations (Scopus)

Abstract

Two-stage Kalman filter based estimation algorithm was developed for wind speed and UAV motion parameters. In the first stage., wind speed estimation algorithm is used based on GPS measurements and dynamic pressure measurements. The wind speed is estimated by Kalman filter using GPS and Air Data System (ADS)measurements. For this purpose., Extended Kalman Filter (EKF)was designed., and as state variables., the wind velocity components and ADS pitot scale factor are considered. In the second stage., the state parameters of the UAV dynamic model are estimated using GPS and IMU measurements. The second stage filter uses GPS position measurements., IMU orientation angles and speed measurements as well as the wind speed value estimated by the first stage filter.

Original language	English
Title of host publication	Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019
Editors	S. Menekay, O. Cetin, O. Alparslan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	875-880
Number of pages	6
ISBN (Electronic)	9781538694480
DOIs	https://doi.org/10.1109/RAST.2019.8767886
Publication status	Published - Jun 2019
Event	9th International Conference on Recent Advances in Space Technologies, RAST 2019 - Istanbul, Turkey Duration: 11 Jun 2019 → 14 Jun 2019

Publication series

Name	Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019

Conference

Conference	9th International Conference on Recent Advances in Space Technologies, RAST 2019
Country/Territory	Turkey
City	Istanbul
Period	11/06/19 → 14/06/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

GPS
Kalman filter
Pitot Tube
Unmanned Aerial Vehicle
Wind speed

Access to Document

10.1109/RAST.2019.8767886

Cite this

Hajiyev, C., Cilden-Guler, D., & Hacizade, U. (2019). Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements. In S. Menekay, O. Cetin, & O. Alparslan (Eds.), Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019 (pp. 875-880). Article 8767886 (Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RAST.2019.8767886

Hajiyev, Chingiz ; Cilden-Guler, Demet ; Hacizade, Ulviye. / Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements. Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019. editor / S. Menekay ; O. Cetin ; O. Alparslan. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 875-880 (Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019).

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title = "Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements",

abstract = "Two-stage Kalman filter based estimation algorithm was developed for wind speed and UAV motion parameters. In the first stage., wind speed estimation algorithm is used based on GPS measurements and dynamic pressure measurements. The wind speed is estimated by Kalman filter using GPS and Air Data System (ADS)measurements. For this purpose., Extended Kalman Filter (EKF)was designed., and as state variables., the wind velocity components and ADS pitot scale factor are considered. In the second stage., the state parameters of the UAV dynamic model are estimated using GPS and IMU measurements. The second stage filter uses GPS position measurements., IMU orientation angles and speed measurements as well as the wind speed value estimated by the first stage filter.",

keywords = "GPS, Kalman filter, Pitot Tube, Unmanned Aerial Vehicle, Wind speed",

author = "Chingiz Hajiyev and Demet Cilden-Guler and Ulviye Hacizade",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 9th International Conference on Recent Advances in Space Technologies, RAST 2019 ; Conference date: 11-06-2019 Through 14-06-2019",

year = "2019",

month = jun,

doi = "10.1109/RAST.2019.8767886",

language = "English",

series = "Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "875--880",

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Hajiyev, C , Cilden-Guler, D & Hacizade, U 2019, Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements. in S Menekay, O Cetin & O Alparslan (eds), Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019., 8767886, Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019, Institute of Electrical and Electronics Engineers Inc., pp. 875-880, 9th International Conference on Recent Advances in Space Technologies, RAST 2019, Istanbul, Turkey, 11/06/19. https://doi.org/10.1109/RAST.2019.8767886

Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements. / Hajiyev, Chingiz ; Cilden-Guler, Demet; Hacizade, Ulviye.
Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019. ed. / S. Menekay; O. Cetin; O. Alparslan. Institute of Electrical and Electronics Engineers Inc., 2019. p. 875-880 8767886 (Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019).

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

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AB - Two-stage Kalman filter based estimation algorithm was developed for wind speed and UAV motion parameters. In the first stage., wind speed estimation algorithm is used based on GPS measurements and dynamic pressure measurements. The wind speed is estimated by Kalman filter using GPS and Air Data System (ADS)measurements. For this purpose., Extended Kalman Filter (EKF)was designed., and as state variables., the wind velocity components and ADS pitot scale factor are considered. In the second stage., the state parameters of the UAV dynamic model are estimated using GPS and IMU measurements. The second stage filter uses GPS position measurements., IMU orientation angles and speed measurements as well as the wind speed value estimated by the first stage filter.

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Hajiyev C , Cilden-Guler D, Hacizade U. Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements. In Menekay S, Cetin O, Alparslan O, editors, Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 875-880. 8767886. (Proceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019). doi: 10.1109/RAST.2019.8767886

Two-stage Kalman filter for estimation of wind speed and UAV flight parameters based on GPS/INS and pitot tube measurements

Abstract

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Bibliographical note

Keywords

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