Wind component estimation for UAS flying in turbulent air

Caterina Grillo, Fernando Montano

Risultato della ricerca: Article

1 Citazione (Scopus)

Abstract

One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.
Lingua originaleEnglish
pagine (da-a)105317-
Numero di pagine7
RivistaAerospace Science and Technology
Volume93
Stato di pubblicazionePublished - 2019

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Extended Kalman filters
Air
Identification (control systems)
Tuning

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

Cita questo

Wind component estimation for UAS flying in turbulent air. / Grillo, Caterina; Montano, Fernando.

In: Aerospace Science and Technology, Vol. 93, 2019, pag. 105317-.

Risultato della ricerca: Article

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