Aiming at the situation that there are correlations among SCADA measurements, this paper proposes a cubature kalman filter method for power system dynamic state estimation considering SCADA measurement correlation. First, this paper analyses the reason of measurement correlation. Then the process noise covariance matrix is derived through state transition equation, and cubature transformation is used to calculate the measurement error covariance matrix. The dynamic state estimation process of power system considering measurement correlation is proposed, and the measurement error covariance matrix and process noise covariance matrix are corrected in real time for each estimation. The simulation results on IEEE-39 system demonstrate that the proposed method can significantly improve the accuracy of state estimation results compared with the cubature kalman filter algorithm without considering measurement correlation.