Aiming at the problem that the external parameters of the on-vehicle 3D LIDAR needs to be calibrated before installation, a calibration method for LIDAR external parameters is proposed under the consideration of LADAR's invisible scanning beam and multi-line scanning. Firstly, scanning a ordinary carton, and the random sample consensus algorithm (RANSAC) is used to fit the initial model of three planes in the obtained point cloud data, with the vertical relationship between the two sides of the carton and the ground as a constraint. Then the rotation and translation steps are used to optimize the fitting precision of the plane model, and the corresponding vector and point are extracted from the optimal model. Next, solving the rotation and translation parameters of the LIDAR using the transformation model of 3D coordinate system based on space vector, calibration of all external parameters can be done by collecting data once. Finally, the effectiveness of the algorithm is verified by the simulation and the results of 3D reconstruction of the outdoor environment after calibration.