Aircraft Air Data Estimation Using a Model-Based Approach

John T. Pearson; R. M. Goodall; M. Eastham

doi:10.3182/20070625-5-FR-2916.00095

Aircraft Air Data Estimation Using a Model-Based Approach

John T. Pearson, R. M. Goodall, M. Eastham

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

1 Citation (Scopus)

Abstract

Air data consists of flight parameters such as pressure altitude, Mach number, angle of attack and angle of sideslip. Traditionally these are derived from measurements of local pressures and local flow angles on the fuselage using external air data probes and vanes. This paper describes the formulation of a Kalman Filter for the estimation of aircraft air data states associated with the pitch aerodynamics. The mathematical model of the aircraft embedded within the Kalman Filter contains the highly non-linear aerodynamic coefficients for the pitch dynamics of the aircraft. A selection of results from a comprehensive simulation assessment are also presented.

Original language	English
Title of host publication	17th IFAC Symposium on Automatic Control in Aerospace
Publisher	Elsevier
Pages	557-562
Number of pages	6
Volume	40
Edition	7
ISBN (Print)	9783902661241, 9781605607344
DOIs	https://doi.org/10.3182/20070625-5-FR-2916.00095
Publication status	Published - 1 Dec 2007
Externally published	Yes
Event	17th IFAC Symposium on Automatic Control in Aerospace - Toulouse, France Duration: 25 Jun 2007 → 29 Jun 2007 Conference number: 17 https://www.sciencedirect.com/journal/ifac-proceedings-volumes/vol/40/issue/7?page=2

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Publisher	Elsevier
Number	7
Volume	40
ISSN (Print)	1474-6670

Conference

Conference	17th IFAC Symposium on Automatic Control in Aerospace
Abbreviated title	ACA' 2007
Country/Territory	France
City	Toulouse
Period	25/06/07 → 29/06/07
Internet address	https://www.sciencedirect.com/journal/ifac-proceedings-volumes/vol/40/issue/7?page=2

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Cite this

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title = "Aircraft Air Data Estimation Using a Model-Based Approach",

abstract = "Air data consists of flight parameters such as pressure altitude, Mach number, angle of attack and angle of sideslip. Traditionally these are derived from measurements of local pressures and local flow angles on the fuselage using external air data probes and vanes. This paper describes the formulation of a Kalman Filter for the estimation of aircraft air data states associated with the pitch aerodynamics. The mathematical model of the aircraft embedded within the Kalman Filter contains the highly non-linear aerodynamic coefficients for the pitch dynamics of the aircraft. A selection of results from a comprehensive simulation assessment are also presented.",

keywords = "Aerospace, Estimation, Flight control, Kalman filters, Sensor fusion",

author = "Pearson, {John T.} and Goodall, {R. M.} and M. Eastham",

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booktitle = "17th IFAC Symposium on Automatic Control in Aerospace",

address = "Netherlands",

edition = "7",

note = "17th IFAC Symposium on Automatic Control in Aerospace, ACA' 2007 ; Conference date: 25-06-2007 Through 29-06-2007",

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Pearson, JT, Goodall, RM & Eastham, M 2007, Aircraft Air Data Estimation Using a Model-Based Approach. in 17th IFAC Symposium on Automatic Control in Aerospace. 7 edn, vol. 40, IFAC Proceedings Volumes (IFAC-PapersOnline), no. 7, vol. 40, Elsevier, pp. 557-562, 17th IFAC Symposium on Automatic Control in Aerospace, Toulouse, France, 25/06/07. https://doi.org/10.3182/20070625-5-FR-2916.00095

Aircraft Air Data Estimation Using a Model-Based Approach. / Pearson, John T.; Goodall, R. M.; Eastham, M.

17th IFAC Symposium on Automatic Control in Aerospace. Vol. 40 7. ed. Elsevier, 2007. p. 557-562 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 40, No. 7).

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

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N1 - Conference code: 17

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N2 - Air data consists of flight parameters such as pressure altitude, Mach number, angle of attack and angle of sideslip. Traditionally these are derived from measurements of local pressures and local flow angles on the fuselage using external air data probes and vanes. This paper describes the formulation of a Kalman Filter for the estimation of aircraft air data states associated with the pitch aerodynamics. The mathematical model of the aircraft embedded within the Kalman Filter contains the highly non-linear aerodynamic coefficients for the pitch dynamics of the aircraft. A selection of results from a comprehensive simulation assessment are also presented.

AB - Air data consists of flight parameters such as pressure altitude, Mach number, angle of attack and angle of sideslip. Traditionally these are derived from measurements of local pressures and local flow angles on the fuselage using external air data probes and vanes. This paper describes the formulation of a Kalman Filter for the estimation of aircraft air data states associated with the pitch aerodynamics. The mathematical model of the aircraft embedded within the Kalman Filter contains the highly non-linear aerodynamic coefficients for the pitch dynamics of the aircraft. A selection of results from a comprehensive simulation assessment are also presented.

KW - Aerospace

KW - Estimation

KW - Flight control

KW - Kalman filters

KW - Sensor fusion

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U2 - 10.3182/20070625-5-FR-2916.00095

DO - 10.3182/20070625-5-FR-2916.00095

M3 - Conference contribution

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SN - 9783902661241

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T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)

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BT - 17th IFAC Symposium on Automatic Control in Aerospace

PB - Elsevier

T2 - 17th IFAC Symposium on Automatic Control in Aerospace

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ER -

Aircraft Air Data Estimation Using a Model-Based Approach

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