An LSTM neural network trained on simulated quadcopter states estimates turbulent wind velocities with lower mean and variance errors than a tilt-angle wind triangle method.
Modeling of urban wind field effects on unmanned rotorcraft flight,
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Wind Estimation Using Quadcopter Motion: A Machine Learning Approach
An LSTM neural network trained on simulated quadcopter states estimates turbulent wind velocities with lower mean and variance errors than a tilt-angle wind triangle method.