Wind field estimation for small unmanned aerial vehicles

Jack W. Langelaan; Nicholas Alley; James Neidhoefer

doi:10.2514/6.2010-8177

Wind field estimation for small unmanned aerial vehicles

Jack W. Langelaan, Nicholas Alley, James Neidhoefer

Aerospace Engineering

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

35 Scopus citations

Abstract

This paper describes a method for estimating wind field (wind velocity, rate of change of wind velocity and wind gradient) for small and mini unmanned aerial vehicles. The approach utilizes sensors which are already part of a standard autopilot sensor suite (GPS, inertial measurement unit, airspeed, magnetometer). The primary motivation is enabling energy harvesting; a secondary motivation is development of a low-cost atmospheric measurement and sampling system. The paper presents an error analysis and discusses the primary contributions to error in the estimated wind field. Results of Monte Carlo simulations compare predicted errors in wind estimates with actual errors and show the effect of using estimated winds for energy harvesting from gusts.

Original language	English (US)
Title of host publication	AIAA Guidance, Navigation, and Control Conference
DOIs	https://doi.org/10.2514/6.2010-8177
State	Published - 2010
Event	AIAA Guidance, Navigation, and Control Conference - Toronto, ON, Canada Duration: Aug 2 2010 → Aug 5 2010

Publication series

Name	AIAA Guidance, Navigation, and Control Conference

Other

Other	AIAA Guidance, Navigation, and Control Conference
Country/Territory	Canada
City	Toronto, ON
Period	8/2/10 → 8/5/10

All Science Journal Classification (ASJC) codes

Aerospace Engineering
Control and Systems Engineering

Access to Document

10.2514/6.2010-8177

Cite this

@inproceedings{09f42c9c021d47e5bfaff41fbfccd65f,

title = "Wind field estimation for small unmanned aerial vehicles",

abstract = "This paper describes a method for estimating wind field (wind velocity, rate of change of wind velocity and wind gradient) for small and mini unmanned aerial vehicles. The approach utilizes sensors which are already part of a standard autopilot sensor suite (GPS, inertial measurement unit, airspeed, magnetometer). The primary motivation is enabling energy harvesting; a secondary motivation is development of a low-cost atmospheric measurement and sampling system. The paper presents an error analysis and discusses the primary contributions to error in the estimated wind field. Results of Monte Carlo simulations compare predicted errors in wind estimates with actual errors and show the effect of using estimated winds for energy harvesting from gusts.",

author = "Langelaan, {Jack W.} and Nicholas Alley and James Neidhoefer",

note = "Funding Information: This research was funded by the Office of Naval Research under Contract Number N00014-09-M-0307. The authors also thank Dan Kuehme for assistance in running simulations.; AIAA Guidance, Navigation, and Control Conference ; Conference date: 02-08-2010 Through 05-08-2010",

year = "2010",

doi = "10.2514/6.2010-8177",

language = "English (US)",

isbn = "9781600869624",

series = "AIAA Guidance, Navigation, and Control Conference",

booktitle = "AIAA Guidance, Navigation, and Control Conference",

}

TY - GEN

T1 - Wind field estimation for small unmanned aerial vehicles

AU - Langelaan, Jack W.

AU - Alley, Nicholas

AU - Neidhoefer, James

N1 - Funding Information: This research was funded by the Office of Naval Research under Contract Number N00014-09-M-0307. The authors also thank Dan Kuehme for assistance in running simulations.

PY - 2010

Y1 - 2010

N2 - This paper describes a method for estimating wind field (wind velocity, rate of change of wind velocity and wind gradient) for small and mini unmanned aerial vehicles. The approach utilizes sensors which are already part of a standard autopilot sensor suite (GPS, inertial measurement unit, airspeed, magnetometer). The primary motivation is enabling energy harvesting; a secondary motivation is development of a low-cost atmospheric measurement and sampling system. The paper presents an error analysis and discusses the primary contributions to error in the estimated wind field. Results of Monte Carlo simulations compare predicted errors in wind estimates with actual errors and show the effect of using estimated winds for energy harvesting from gusts.

AB - This paper describes a method for estimating wind field (wind velocity, rate of change of wind velocity and wind gradient) for small and mini unmanned aerial vehicles. The approach utilizes sensors which are already part of a standard autopilot sensor suite (GPS, inertial measurement unit, airspeed, magnetometer). The primary motivation is enabling energy harvesting; a secondary motivation is development of a low-cost atmospheric measurement and sampling system. The paper presents an error analysis and discusses the primary contributions to error in the estimated wind field. Results of Monte Carlo simulations compare predicted errors in wind estimates with actual errors and show the effect of using estimated winds for energy harvesting from gusts.

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U2 - 10.2514/6.2010-8177

DO - 10.2514/6.2010-8177

M3 - Conference contribution

AN - SCOPUS:79955771405

SN - 9781600869624

T3 - AIAA Guidance, Navigation, and Control Conference

BT - AIAA Guidance, Navigation, and Control Conference

T2 - AIAA Guidance, Navigation, and Control Conference

Y2 - 2 August 2010 through 5 August 2010

ER -

Wind field estimation for small unmanned aerial vehicles

Abstract

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All Science Journal Classification (ASJC) codes

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