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Aiming at the requirements of real-time path planning and autonomous capability for adapting to the environmental changes of Unmanned Aerial Vehicle (UAV), a new method for wind estimation and airspeed calibration is proposed. Based on the information of GPS receiver, air data computer and magnetic compass, the method is implemented. Aiming at constant wind mode, the wind speed and wind direction can be estimated using velocity triangle vector between ground speed, wind speed and airspeed. A Derivative-free extended Kalman filter (DEKF) is applied to estimate wind parameters and scaling factor of airspeed. Using a digital simulation platform for Unmanned Aerial Vehicle (UAV), an entire autonomic flight simulation were achieved in 2D wind field. Simulations results show that wind speed and wind direction can be accurately estimated both in straight line and turning segment during the path tracking by using the method.