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A Novel Estimation Method of Wind Speed and Direction Based on GNSS/INS/ADS Integrated Navigation
Author(s) -
Jingjuan Zhang,
Hao Cong,
Xueyun Wang
Publication year - 2021
Publication title -
journal of sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.399
H-Index - 43
eISSN - 1687-7268
pISSN - 1687-725X
DOI - 10.1155/2021/6844509
Subject(s) - gnss applications , computer science , estimation , wind speed , navigation system , inertial navigation system , remote sensing , global positioning system , geodesy , engineering , real time computing , geography , telecommunications , meteorology , physics , inertial frame of reference , systems engineering , quantum mechanics
Arriving on time is of great importance for flight management and passenger experience. One of the essential factors that impacts on-time arrival is the wind condition. Accurate information of wind speed and direction around the fuselage helps to improve the performance of on-time arrival and four-dimensional trajectory (4DT) planning. To determine accurate wind information in real-time, a novel airborne estimation method of wind speed and direction is proposed in this paper. Inertial Navigation System (INS), Global Satellite Navigation System (GNSS), and Air Data System (ADS) are fused in an Unscented Kalman Filter (UKF), which provides great accuracy and robustness in nonlinearity conditions. The dynamic models of wind are established, and implementations of the UKF are detailed. Finally, simulations are designed and the effectiveness of the proposed method is verified through the comparison with the traditional direct measurement method. Results demonstrate that the accuracy of wind speed and direction obtained by our method is nearly two times higher than the traditional direct measurement method.

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