Low-cost pressure sensor, which provides airspeed measurements for low-cost UAV, is vulnerable to disturbance which causes drift of outputs; this will directly affect the flight safety. To solve this problem, two practical airspeed measurement calibration schemes were proposed based on the measurement of attitude, heading, ground speed and airspeed, the airspeed drift and the wind speed can be estimated by Kalman filter. When the heading measurement was not available, additional heading estimation algorithm was used based on the ground speed measurement. Finally, Monte Carlo simulations and flight test were performed to validate the proposed algorithm, and the algorithm's observability was analyzed.