A model predictive control (MPC) method based on extended state Kalman filter (ESKF) is proposed for the path tracking control problem of a quadrotor UAV that is susceptible to wind disturbance and measurement noise during flight. First, the Newton-Euler method is used to establish a four-rotor UAV dynamic model under the influence of wind disturbance; then, an MPC method based on the error model is used for position control, and an ESKF is proposed to estimate wind field disturbance to compensate the controller. The attitude dynamic model is linearized by the feedback linearization method, and an attitude controller based on ESKF-MPC is designed. Finally, the simulation results show that when the measurement noise variance is 0. 000 1, the position tracking mean square error of this method is 0. 013 meters which is smaller than that of the active disturbance rejection control method. When the variance is greater than 0. 000 1, the active disturbance rejection control method makes the system unstable, and the method in this paper can achieve better position tracking.