Due to the difficulty of obtaining real-time air data like wind speed and angle of attack, the LSTM (Long Short-Term Memory) network is employed to extract these parameters from the FADS (Flush Air Data Sensing System), thereby enhancing the performance of the UAV (Unmanned Aerial Vehicle) flight control system. Real-time surface pressure data from the UAV is collected through the FADS system, and LSTM is utilized to estimate parameters like airspeed and AoA (angle of attack). First, the configuration of the FADS system is presented, followed by the application of LSTM to derive air data from FADS, and further integration of INS (Inertial Navigation System) data to estimate wind speed. Simulation is implemented, and the results demonstrate that the proposed method provides precise wind speed estimations, AoA, and related data, which can be utilized for UAV flight control. Finally, a summary and outlook of this research are provided.