Stochastic Spatial Wind Field Simulation using a Potential Field

A new simulation environment is proposed, featuring the generation of unique spatial wind velocity fields using stochastic methods. This wind field simulation technique can be tuned to match realistic atmospheric conditions based on weather data measurements at a desired location. The proposed simulation environment also includes an aircraft dynamic model of a research unmanned aerial vehicle and corresponding sensor error modeling. The parameters of the aircraft model were determined from previous studies utilizing experimental flight data. The new simulator is used to validate the effectiveness of a nonlinear Kalman filtering based wind estimation algorithm.

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