Aiming at the solving the problem of measurement error from the geometric error calibration in equipment assembly. A calibration algorithm based on improved particle swarm is proposed for the calibration of geometric parameters of 3D laser scanner with orthogonal axes. First, the geometric error parameters to be optimized are constructed based on the improved DH parameter model of the 3D scanning equipment, and the particle swarm algorithm is used to perform iterative optimization within the constraints to determine the calibration value. Then, on the basis of traditional particle swarm optimization, the optimization of dynamic parameters (inertia weight, dynamic adjustment of learning factor and fitness function improvement based on dynamic plane fitting of global least squares algorithm) is carried out to solve the problem that the algorithm falls into local optimum. At last, three different methods are used to carry out the calibration experiments based on the standard checkerboard calibration board. The comparative analysis of the experimental results shows that the dynamic plane fitting-parameter improvement PSO algorithm proposed in this paper greatly improves the convergence speed of the calibration algorithm and the reliability of the fitness calculation, and can quickly calibrate the equipment. The accuracy is also greatly improved. This calibration method provides a reference for the calibration of geometric parameters of other orthogonal axis systems.