The measurement system consisted of vision and 3D laser ranging is the main sensing device for motion estimation and environment modeling. To realize the unification of the sensing data coordinate system of the measurement system, a method for calibrating the structural parameters of the vision and 3D laser ranging system based on the self-combination of space vectors is proposed in this article. It mainly includes three aspects: 1) The plane calibration method is used to solve the internal parameters of the camera and the normal vector of the plane target in the camera coordinate system and the plane iterative fitting algorithm is utilized to solve the normal vector of the plane target in the LiDAR coordinate system. The plane target normal vector set is established under two coordinate systems. 2) According to the angle between the vectors, the cross vector is independently selected in the plane target normal vector combination, and the structural parameter calibration parameters are established to solve the objective function, and the calibration objective function of structure parameters is established. 3) The nonlinear optimization algorithm is used to solve the least-squares problem and obtain the optimal estimation of external parameters. The effectiveness and accuracy of the method are evaluated by simulation and actual calibration experiments. Results show that the error between the image object-side projection and the 3D point cloud of this method is less than 30 mm (3σ), which not only satisfies high-precision 3D measurement but also has a high calibration efficiency. It meets the requirements of accurate measurement of sensor fusion measurement.