Abstract: Three observation points method is a traditional realtime way for calculating attitude angles of yaw, pitch and roll. Measurement asynchronism of three observation points will lead to large error of attitude angles during tunneling. In order to improve the measurement precision, Kalman filtering method is proposed to predict the coordination of observation points. Firstly, the system state equation and measurement equation are established to describe the movement state of the system. Secondly, the covariance of system noise matrix and measurement noise matrix are estimated to express the random noise of the system. Finally, coordinates of the observation points are predicted recursively. Monte Calro simulation results show that the performance of this method is better than those traditional methods. Both the simulation experiment and measurement experiment successfully demonstrated the proposed algorithm has the advantages of greatly decreasing the error for attitude angles, and inhibiting the effect of measurement error caused by random noise.