Flight Testing an Integrated Wind/Airdata- and Navigation System for General Aviation Aircraft

Myschik, Stephan; Sachs, Gottfried

doi:10.2514/6.2007-6796

Cited by 14 publications

(6 citation statements)

References 5 publications

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“…11 Myschik discusses an integrated wind estimation/navigation system for use on general aviation aircraft. 12,13 de Divitiis describes a variational technique for wind estimation for a small ducted fan vehicle. 14…”

Section: Introductionmentioning

confidence: 99%

Wind Field Estimation for Small Unmanned Aerial Vehicles

Langelaan

Alley

Neidhoefer

2011

Journal of Guidance, Control, and Dynamics

221

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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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Section: Introductionmentioning

confidence: 99%

Wind Field Estimation for Small Unmanned Aerial Vehicles

Langelaan

Alley

Neidhoefer

2011

Journal of Guidance, Control, and Dynamics

221

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“…A large amount of research has been conducted on wind estimation. The main existing methods can be categorized into two types based on whether they depend on knowledge of the aircraft aerodynamic model or not, i.e., model-aided methods (e.g., [5,6]) and model-free ones. For aircraft system identification applications, since the overall goal is to model the aircraft aerodynamics, it is necessary to consider the aerodynamic model as unknown for the wind estimation problem.…”

Section: Introductionmentioning

confidence: 99%

Wind and Airflow Angle Estimation Using an Adaptive Extended Rauch-Tung-Striebel Smoother

Fang

Visser

Pool

et al. 2022

AIAA SCITECH 2022 Forum

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This paper proposes a new method that estimates the three-dimensional stochastic wind velocity for an aircraft equipped with a Pitot-static tube and airflow vanes. Since the performance of most state estimators, e.g., the extended Rauch-Tung-Striebel smoother, relies on the process and measurement noise covariance settings, the proposed method employs the expectationmaximization approach to estimate the noise covariance matrices to improve the estimation accuracy. Numerical simulations demonstrated that the proposed method can successfully estimate the noise covariance matrices, especially for the noise covariance of the wind velocity, using the measurement data and reconstruct the wind velocity offline. Additionally, the smoothed true airspeed, angle of attack, and angle of sideslip data are more accurate compared to the direct measurements. This feature is also beneficial for other applications such as the aerodynamic model identifications of aircraft.

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“…Most research studies reported in the literature considering only deterministic wind component assume constant wind. 4,6,7,10 Others model deterministic wind component as a time-varying function such as triangular wave form 5 or a polynomial function. 9 In applications where trajectory of aircraft is in question or the wind exposure may vary based on position, wind model as function of time is not adequate.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. 10 and, 11,12 use an onboard airdata sensor along with GPS/INS unit to estimate wind speed and direction based on aircraft kinematics. Refs.…”

Section: Introductionmentioning

confidence: 99%

Wind Field Estimation and Its Utilization in Trajectory Prediction

Kampoon

Okolo

Erturk

et al. 2015

AIAA Atmospheric Flight Mechanics Conference

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This work develops a method for onboard estimation of wind field with spatial and temporal variation based on local wind vector estimation and/or measurements from multiple aircraft flying in the same airspace. Aircraft flying in the same airspace of operation are considered airborne wind sensors scattered over the airspace because of the fact that aircraft carry along with them wind information inherent in their dynamics and kinematics. The onboard wind field estimation is formulated in the framework of parameter estimation based on various wind field models, which are different function of position and time. The online wind field estimation is utilized in trajectory prediction of aircraft flying in spatially and/or temporally varying wind. Various simulation cases are presented to demonstrate the feasibility of wind field estimation and the benefit of using such information in trajectory prediction.

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Flight Testing an Integrated Wind/Airdata- and Navigation System for General Aviation Aircraft

Cited by 14 publications

References 5 publications

Wind Field Estimation for Small Unmanned Aerial Vehicles

Wind Field Estimation for Small Unmanned Aerial Vehicles

Wind and Airflow Angle Estimation Using an Adaptive Extended Rauch-Tung-Striebel Smoother

Wind Field Estimation and Its Utilization in Trajectory Prediction

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