In the field of fixed-wing unmanned aerial vehicles (UAVs), wind disturbance has a significant impact on flight performance and safety. This paper proposes a simulation method for wind disturbance on fixed-wing UAVs by combining real-world flight data and Kalman filter to make results of simulation more reliable. First, real-world flight data is utilized to extract an accurate wind field model. During this process, the Kalman filter is employed to fuse sensor data, enabling the calculated wind field data to closely approximate the real-world wind conditions. Then, a mathematical model of the fixed-wing UAV is established. Subsequently, the real-world wind field data is incorporated into the UAV simulation process. The comparison between the simulation data and the actual flight data shows that they are quite close, which verifies the authenticity and reliability of the simulation method.