Air Data Estimating of A Small UAV based on Micro Pressure Sensors

The application of small UAV is increasingly widespread, but measuring airflow information of small UAV is still a difficult problem. Inspired by birds, a method to estimate the current airflow information (such as airspeed, angle of attack and sideslip angle) of small UAVs using micro air pressure sensors is proposed. According to the aerodynamic characteristics of the small UAV, the special position for installing the air pressure sensor is selected. The air pressure measurements under different flight conditions are sent into the machine learning model for learning. After learning convergence, the air flow information estimation algorithm with robustness to sensor installation error can be obtained. The machine learning (ML) estimation algorithm can solve the problem that the sensor installation error causes the failure of traditional FADS. The simulation results show that this method can accurately estimate the airflow information.