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  4. Evaluation of Wind Effects on UAV Autonomous Navigation Based on Vehicle Dynamic Model
 
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conference paper

Evaluation of Wind Effects on UAV Autonomous Navigation Based on Vehicle Dynamic Model

Khaghani, Mehran  
•
Skaloud, Jan  
2016
Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)

A novel approach to autonomous navigation for small UAVs was recently introduced by the authors. An abridged description of this approach can be found in present paper, with its main contribution being further evaluation of effects of wind on navigation performance. The vehicle dynamic model (VDM) serves as the main process model within the introduced navigation filter. The proposed method exploits the knowledge of physical properties of the UAV together with control input with the goal to significantly increase the accuracy and reliability of autonomous navigation. This is especially relevant for small UAVs with low-cost IMUs on-board and no extra sensor added to the conventional INS/GNSS setup. The improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Robustness and scalability of the navigation system against random changes in wind velocity are investigated via Monte Carlo simulations using real 3D wind velocity data. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to conventional kinematic modeling in INS/GNSS integration. Simulations also reveal that navigation errors are almost doubled as wind velocity doubles, which gives an estimation of the scalability of the navigation system.

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Type
conference paper
Web of Science ID

WOS:000391479501046

Author(s)
Khaghani, Mehran  
•
Skaloud, Jan  
Date Issued

2016

Publisher

Inst Navigation

Publisher place

Washington

Published in
Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)
Total of pages

9

Start page

1432

End page

1440

Subjects

UAV

•

Wind estimation

•

Autonomous navigation

•

Vehicle dynamic model

•

GNSS outage

•

Inertial navigation

•

topotraj

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
TOPO  
Available on Infoscience
August 31, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/128991
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