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Most aircrafts are equipped with an air data system to measure airspeed, angle-of-sideslip(AOS) and so on. An air data system consists of Pitot-static tube and gimbal-mounted weathervane. The static pressure obtained by Pitot-static tube is affected by fuselage nose and angle-of-attack(AOA). To measure AOA and AOS accurately, weathervane should be placed out of boundary layer around fuselage nose. But due to structural problems, it is not easy to keep sufficient distance between static-hole of Pitot-static tube and fuselage nose. This gives rise to the error of measured air data and it is difficult to correct this error by wind-tunnel test or computational method. Thus, air data system must be calibrated through flight test after installation. This paper proposes the Kalman filter setup to calibrate static pressure, or airspeed and barometric altitude using GPS ground velocity. And also Kalman filter based AOS calibration method is proposed using flight data. Proposed methods are verified by simulation and real flight data of Smart UAV.