@inproceedings{6e7c79b42ff04e76b114e01e347558c5,
title = "Kalman Filter-based Wind Estimation for Forest Fire Monitoring with a Quadrotor UAV",
abstract = "A Kalman filter-based wind estimation method is presented in this paper for wildfire monitoring. Wind behavior is one of the key factors in fire propagation, especially on the early stage of a fire. This quadrotor UAV-based method is proposed to estimate the lateral wind in the fire environment only with a standard autopilot sensor suite on board. A Kalman filter is designed to estimate the wind vector based on the vehicle's hovering inclined angle in the wind environment. The designed Kalman filter can reduce the influence of sensor noises and improve the accuracy of the wind estimation. The effectiveness of the algorithm is demonstrated in a simulation environment.",
author = "Zhewen Xing and Youmin Zhang and Su, {Chun Yi} and Yaohong Qu and Ziquan Yu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 3rd IEEE Conference on Control Technology and Applications, CCTA 2019 ; Conference date: 19-08-2019 Through 21-08-2019",
year = "2019",
month = aug,
doi = "10.1109/CCTA.2019.8920637",
language = "英语",
series = "CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "783--788",
booktitle = "CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications",
}