The position-pose relation between cameras is the main factor that affects the accuracy of an image-based ballastless track subgrade monitoring system. Each camera in the monitoring station must face the corresponding monitoring target surface, so there is often no public field of view between the cameras. According to the equivalence between the hand-eye calibration problem in robot vision and the calibration of position-pose relation between cameras, a position-pose calibration method based on feature points is proposed. Four feature points with square distribution are set on the monitoring target surface. A set of cameras is moved twice in small step and takes the pictures of the target surface in three different positions. The P4P (perspective-four-point) algorithm is used to solve the position-pose relation between the camera and the target, and then obtains the movement trajectory of the camera. The matrix rearrangement method is used to obtain the pose conversion matrix between the cameras, and the Levenberg-Marquardt algorithm is used for nonlinear optimization. Simulation results indicate that the angle error is less than 0.03° and the translation error is less than 0.3 cm when the noise variance is less than 1 pixel. The effectiveness and practicability of the method in this paper are verified by simulation, and the method in this paper can meet the needs of the settlement measurement of the ballastless track subgrade.