Obtaining accurate real-time vehicle status information is an important prerequisite for decision-making and control of formula student autonomous racing, but some status information is difficult to obtain in real time through direct measurement. To address these issues, this paper presents a method for state estimation of formula student autonomous racing based on a three-degree-of-freedom model of the vehicle using the extended Kalman filter which is validated and analyzed by joint simulation with CarSim and MATLAB/Simulink. The results show that the scheme can estimate the sideslip angle and yaw angular velocity of the racing in real time and more accurately, and the estimation results provide a parametric basis for the racing control system.