TY - GEN
T1 - Wind Estimation with UAVs Using Improved Adaptive Kalman Filter
AU - Qu, Yaohong
AU - Wang, Kai
AU - Wu, Xiwei
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - This paper presents an improved adaptive Kalman filter algorithm for wind estimation with unmanned aerial vehicles (UAVs). The wind measurement values with UAVs always include large continuous outlier. At the same time, the noise statistical prior knowledge for wind is insufficient. Firstly, the wind state equation including mean wind and turbulence is established by accurate wind model. Then the three-dimensional measurement equation of wind is established based on the principle of the wind measurement by UAVs. Finally, the wind data measured by the UAVs is processed using improved adaptive Kalman filter. Simulation results demonstrate the feasibility of the approach. And compared with the traditional Kalman filter and the adaptive Kalman filter, the proposed algorithm can reduce the influence of large continuous outliers and ensure the accuracy of wind field estimation.
AB - This paper presents an improved adaptive Kalman filter algorithm for wind estimation with unmanned aerial vehicles (UAVs). The wind measurement values with UAVs always include large continuous outlier. At the same time, the noise statistical prior knowledge for wind is insufficient. Firstly, the wind state equation including mean wind and turbulence is established by accurate wind model. Then the three-dimensional measurement equation of wind is established based on the principle of the wind measurement by UAVs. Finally, the wind data measured by the UAVs is processed using improved adaptive Kalman filter. Simulation results demonstrate the feasibility of the approach. And compared with the traditional Kalman filter and the adaptive Kalman filter, the proposed algorithm can reduce the influence of large continuous outliers and ensure the accuracy of wind field estimation.
KW - Adaptive Kalman Filter
KW - UAVs
KW - Wind Estimation
UR - http://www.scopus.com/inward/record.url?scp=85073095065&partnerID=8YFLogxK
U2 - 10.1109/CCDC.2019.8832809
DO - 10.1109/CCDC.2019.8832809
M3 - 会议稿件
AN - SCOPUS:85073095065
T3 - Proceedings of the 31st Chinese Control and Decision Conference, CCDC 2019
SP - 3660
EP - 3665
BT - Proceedings of the 31st Chinese Control and Decision Conference, CCDC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 31st Chinese Control and Decision Conference, CCDC 2019
Y2 - 3 June 2019 through 5 June 2019
ER -